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  • 1. Andrée, Martin
    et al.
    Paasch, Jesper M.
    Paulsson, Jenny
    Seipel, Stefan
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    BIM and 3D property visualisation2018In: Proc. FIG Congress 2018, 2018, article id 9367Conference paper (Refereed)
  • 2. Aslani, Mohammad
    et al.
    Mesgari, Mohammad Saadi
    Seipel, Stefan
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Wiering, Marco
    Developing adaptive traffic signal control by actor-critic and direct exploration methods2019In: Proceedings of the Institution of Civil Engineers: Transport, ISSN 0965-092X, E-ISSN 1751-7710, Vol. 172, no 5, p. 289-298Article in journal (Refereed)
  • 3. Aslani, Mohammad
    et al.
    Seipel, Stefan
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. University of Gävle.
    A fast instance selection method for support vector machines in building extraction2020In: Applied Soft Computing, ISSN 1568-4946, E-ISSN 1872-9681, Vol. 97, article id 106716Article in journal (Refereed)
    Abstract [en]

    Training support vector machines (SVMs) for pixel-based feature extraction purposes from aerial images requires selecting representative pixels (instances) as a training dataset. In this research, locality-sensitive hashing (LSH) is adopted for developing a new instance selection method which is referred to as DR.LSH. The intuition of DR.LSH rests on rapidly finding similar and redundant training samples and excluding them from the original dataset. The simple idea of this method alongside its linear computational complexity make it expeditious in coping with massive training data (millions of pixels). DR.LSH is benchmarked against two recently proposed methods on a dataset for building extraction with 23,750,000 samples obtained from the fusion of aerial images and point clouds. The results reveal that DR.LSH outperforms them in terms of both preservation rate and maintaining the generalization ability (classification loss). The source code of DR.LSH can be found in https://github.com/mohaslani/DR.LSH.

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  • 4.
    Aslani, Mohammad
    et al.
    Univ Gävle, Dept Comp & Geospatial Sci, Gävle, Sweden..
    Seipel, Stefan
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Univ Gävle, Dept Comp & Geospatial Sci, Gävle, Sweden..
    A Spatially Detailed Approach to the Assessment of Rooftop Solar Energy Potential based on LiDAR Data2022In: GISTAM: Proceedings of the 8th International Conference on Geographical Information Systems Theory, Applications and Management / [ed] Cédric Grueau, Lemonia Ragia, Setúbal: SciTePress, 2022, p. 56-63Conference paper (Refereed)
    Abstract [en]

    Rooftop solar energy has long been regarded as a promising solution to cities' growing energy demand and environmental problems. A reliable estimate of rooftop solar energy facilitates the deployment of photovoltaics and helps formulate renewable-related policies. This reliable estimate underpins the necessity of accurately pinpointing the areas utilizable for mounting photovoltaics. The size, shape, and superstructures of rooftops as well as shadow effects are the important factors that have a considerable impact on utilizable areas. In this study, the utilizable areas and solar energy potential of rooftops are estimated by considering the mentioned factors using a three-step methodology. The first step involves training PointNet++, a deep network for object detection in point clouds, to recognize rooftops in LiDAR data. Second, planar segments of rooftops are extracted using clustering. Finally, areas that receive sufficient solar irradiation, have an appropriate size, and fulfill photovoltaic installation requirements are identified using morphological operations and predefined thresholds. The obtained results show high accuracy for rooftop extraction (93%) and plane segmentation (99%). Moreover. the spatially detailed analysis indicates that 17% of rooftop areas are usable for photovoltaics.

  • 5.
    Aslani, Mohammad
    et al.
    Univ Gävle, Dept Comp & Geospatial Sci, Gävle, Sweden..
    Seipel, Stefan
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Univ Gävle, Dept Comp & Geospatial Sci, Gävle, Sweden.
    Automatic identification of utilizable rooftop areas in digital surface models for photovoltaics potential assessment2022In: Applied Energy, ISSN 0306-2619, E-ISSN 1872-9118, Vol. 306, article id 118033Article in journal (Refereed)
    Abstract [en]

    The considerable potential of rooftop photovoltaics (RPVs) for alleviating the high energy demand of cities has made them a proven technology in local energy networks. Identification of rooftop areas suitable for installing RPVs is of importance for energy planning. Having these suitable areas referred to as utilizable areas greatly assists in a reliable estimate of RPVs energy production. Within such a context, this research aims to propose a spatially detailed methodology that involves (a) automatic extraction of buildings footprint, (b) automatic segmentation of roof faces, and (c) automatic identification of utilizable areas of roof faces for solar infrastructure installation. Specifically, the innovations of this work are a new method for roof face segmentation and a new method for the identification of utilizable rooftop areas. The proposed methodology only requires digital surface models (DSMs) as input, and it is independent of other auxiliary spatial data to become more functional. A part of downtown Gothenburg composed of vegetation and high-rise buildings with complex shapes was selected to demonstrate the methodology performance. According to the experimental results, the proposed methodology has a high success rate in building extraction (about 95% correctness and completeness) and roof face segmentation (about 85% completeness and correctness). Additionally, the results suggest that the effects of roof occlusions and roof superstructures are satisfactorily considered in the identification of utilizable rooftop areas. Thus, the methodology is practically effective and relevant for the detailed RPVs assessments in arbitrary urban regions where only DSMs are accessible.

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  • 6.
    Aslani, Mohammad
    et al.
    Department of Computer and Geo-spatial Sciences, University of Gävle, Gävle, Sweden.
    Seipel, Stefan
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction.
    Efficient and decision boundary aware instance selection for support vector machines2021In: Information Sciences, ISSN 0020-0255, E-ISSN 1872-6291, Vol. 577, p. 579-598Article in journal (Refereed)
    Abstract [en]

    Support vector machines (SVMs) are powerful classifiers that have high computational complexity in the training phase, which can limit their applicability to large datasets. An effective approach to address this limitation is to select a small subset of the most representative training samples such that desirable results can be obtained. In this study, a novel instance selection method called border point extraction based on locality-sensitive hashing (BPLSH) is designed. BPLSH preserves instances that are near the decision boundaries and eliminates nonessential ones. The performance of BPLSH is benchmarked against four approaches on different classification problems. The experimental results indicate that BPLSH outperforms the other methods in terms of classification accuracy, preservation rate, and execution time. The source code of BPLSH can be found in https://github.com/mohaslani/BPLSH. 

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  • 7.
    Aslani, Mohammad
    et al.
    Univ Gävle, Dept Comp & Geospatial Sci, Gävle, Sweden..
    Seipel, Stefan
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division Vi3. Univ Gävle, Dept Comp & Geospatial Sci, Gävle, Sweden..
    Rooftop segmentation and optimization of photovoltaic panel layouts in digital surface models2023In: Computers, Environment and Urban Systems, ISSN 0198-9715, E-ISSN 1873-7587, Vol. 105, article id 102026Article in journal (Refereed)
    Abstract [en]

    Rooftop photovoltaic panels (RPVs) are being increasingly used in urban areas as a promising means of achieving energy sustainability. Determining proper layouts of RPVs that make the best use of rooftop areas is of importance as they have a considerable impact on the RPVs performance in efficiently producing energy. In this study, a new spatial methodology for automatically determining the proper layouts of RPVs is proposed. It aims to both extract planar rooftop segments and identify feasible layouts with the highest number of RPVs in highly irradiated areas. It leverages digital surface models (DSMs) to consider roof shapes and occlusions in placing RPVs. The innovations of the work are twofold: (a) a new method for plane segmentation, and (b) a new method for optimally placing RPVs based on metaheuristic optimization, which best utilizes the limited rooftop areas. The proposed methodology is evaluated on two test sites that differ in urban morphology, building size, and spatial resolution. The results show that the plane segmentation method can accurately extract planar segments, achieving 88.7% and 99.5% precision in the test sites. In addition, the results indicate that complex rooftops are adequately handled for placing RPVs, and overestimation of solar energy potential is avoided if detailed analysis based on panel placement is employed.

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  • 8. Aslani, Mohammad
    et al.
    Seipel, Stefan
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Mesgari, Mohammad Saadi
    Wiering, Marco
    Traffic signal optimization through discrete and continuous reinforcement learning with robustness analysis in downtown Tehran2018In: Advanced Engineering Informatics, ISSN 1474-0346, E-ISSN 1873-5320, Vol. 38, p. 639-655Article in journal (Refereed)
  • 9. Aslani, Mohammad
    et al.
    Seipel, Stefan
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Wiering, Marco
    Continuous residual reinforcement learning for traffic signal control optimization2018In: Canadian journal of civil engineering (Print), ISSN 0315-1468, E-ISSN 1208-6029, Vol. 45, no 8, p. 690-702Article in journal (Refereed)
  • 10.
    Blomqvist, Sven
    et al.
    Univ Gävle, Fac Hlth & Occupat Studies, Gävle, Sweden..
    Seipel, Stefan
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala Univ, Dept Informat Technol, Uppsala, Sweden.;Univ Gävle, Fac Engn & Sustainable Dev, Gävle, Sweden..
    Engstrom, Maria
    Univ Gävle, Fac Hlth & Occupat Studies, Gävle, Sweden..
    Using augmented reality technology for balance training in the older adults: a feasibility pilot study2021In: BMC Geriatrics, E-ISSN 1471-2318, Vol. 21, no 1, article id 144Article in journal (Refereed)
    Abstract [en]

    BackgroundImpaired balance leading to falls is common in the older adults, and there is strong evidence that balance training reduces falls and increases independence. Reduced resources in health care will result in fewer people getting help with rehabilitation training. In this regard, the new technology augmented reality (AR) could be helpful. With AR, the older adults can receive help with instructions and get feedback on their progression in balance training. The purpose of this pilot study was to examine the feasibility of using AR-based visual-interactive tools in balance training of the older adults.MethodsSeven older adults (66-88years old) with impaired balance trained under supervision of a physiotherapist twice a week for six weeks using AR-based visual-interactive guidance, which was facilitated through a Microsoft HoloLens holographic display. Afterwards, participants and physiotherapists were interviewed about the new technology and their experience of the training. Also, fear of falling and balance ability were measured before and after training.ResultsFive participants experienced the new technology as positive in terms of increased motivation and feedback. Experiences were mixed regarding the physical and technical aspects of the HoloLens and the design of the HoloLens application. Participants also described issues that needed to be further improved, for example, the training program was difficult and monotonous. Further, the HoloLens hardware was felt to be heavy, the application's menu was difficult to control with different hand manoeuvres, and the calibration took a long time. Suggestions for improvements were described. Results of the balance tests and self-assessment instruments indicated no improvements in balance performance after AR training.ConclusionsThe study showed that training with the new technology is, to some extent, feasible for the older adults, but needs further development. Also, the technology seemed to stimulate increased motivation, which is a prerequisite for adherence to training. However, the new technology and training requires further development and testing in a larger context.

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  • 11.
    Chandel, Kuhelee
    et al.
    Högskolan i Gävle, Akademin för teknik och miljö.
    Åhlén, Julia
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology.
    Seipel, Stefan
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology. Department of Computer and Geospatial Sciences, University of Gävle, Sweden.
    Augmented Reality and Indoor Positioning in Context of Smart Industry: A Review2022In: Management and Production Engineering Review, ISSN 2080-8208, E-ISSN 2082-1344, Vol. 13, no 4, p. 72-87Article in journal (Refereed)
    Abstract [en]

    Presently, digitalization is causing continuous transformation of industrial processes. However,it does pose challenges like spatially contextualizing data from industrial processes. Thereare various methods for calculating and delivering real-time location data. Indoor positioningsystems (IPS) are one such method, used to locate objects and people within buildings. Theyhave the potential to improve digital industrial processes, but they are currently underutilized.In addition, augmented reality (AR) is a critical technology in today’s digital industrialtransformation. This article aims to investigate the use of IPS and AR in manufacturing,the methodologies and technologies employed, the issues and limitations encountered, andidentify future research opportunities. This study concludes that, while there have been manystudies on IPS and navigation AR, there has been a dearth of research efforts in combiningthe two. Furthermore, because controlled environments may not expose users to the practicalissues they may face, more research in a real-world manufacturing environment is required toproduce more reliable and sustainable results.

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  • 12. Forsberg, A-K
    et al.
    Pettersson, Lars W
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Human-Computer Interaction. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis. Människa-datorinteraktion.
    Lindén, E
    Sandberg, M
    Seipel, Stefan
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology. Interfaculty Units, Centre for Image Analysis. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Human-Computer Interaction. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis. Människa-datorinteraktion.
    An augmented-reality approach to co-located visual exploration of indoor climate data in real rooms.2005In: Proceedings of the 10th International Conference on Indoor Air Quality and Climate: Indoor Air, 2005Conference paper (Refereed)
  • 13.
    Forsell, Camilla
    et al.
    Uppsala University, Humanistisk-samhällsvetenskapliga vetenskapsområdet, Faculty of Social Sciences, Department of Information Science. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Human-Computer Interaction. Människa-datorinteraktion.
    Seipel, Stefan
    Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Human-Computer Interaction.
    Lind, Mats
    Uppsala University, Humanistisk-samhällsvetenskapliga vetenskapsområdet, Faculty of Social Sciences, Department of Information Science. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Human-Computer Interaction. Människa-datorinteraktion.
    Simple 3D glyphs for Spatial Multivariate Data2005In: IEEE Symposium on Information Visualization: InfoVis 05, 2005, p. 244-Conference paper (Refereed)
    Abstract [en]

    We present an effort to evaluate the possible utility of a new type of 3D glyphs intended for visualizations of multivariate spatial data. They are based on results from vision research suggesting that our perception of metric 3D structure is distorted and imprecise relative to the actual scene before us (e.g., [1]); only a class of qualitative properties of the scene is perceived with accuracy. These properties are best characterized as being invariant over affine but not Euclidean transformations. They are related, but not identical to, the non-accidental properties (NAPs) described by Lowe [2] on which the notion of geons is based [3]. A large number of possible 3D glyphs for the visualization of spatial data can be constructed using such properties. One group is based on the local sign of surface curvature. We investigated these properties in a visualization experiment. The results are promising and the implications for visualization are discussed.

  • 14.
    Forsell, Camilla
    et al.
    Uppsala University, Humanistisk-samhällsvetenskapliga vetenskapsområdet, Faculty of Social Sciences, Department of Information Science. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Human-Computer Interaction. Människa-datorinteraktion.
    Seipel, Stefan
    Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Human-Computer Interaction.
    Lind, Mats
    Uppsala University, Humanistisk-samhällsvetenskapliga vetenskapsområdet, Faculty of Social Sciences, Department of Information Science. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Human-Computer Interaction. Människa-datorinteraktion.
    Surface Glyphs for Efficient Visualization of Spatial Multivariate Data2006In: Information Visualization, ISSN 1473-8716, Vol. 5, p. 112-124Article in journal (Refereed)
    Abstract [en]

    We present a first effort to evaluate the possible utility of a new type of surface glyphs intended for visualizations of multivariate spatial data. The glyphs are based on results from vision research suggesting that our perception of metric 3D structure is distorted and imprecise relative to the actual scene before us; only a class of qualitative properties of the scene is perceived with accuracy. These properties are best characterized as being invariant over affine but not Euclidean transformations. A large number of possible 3D glyphs for the visualization of spatial data can be constructed using such properties. One group is based on the local sign of surface curvature. We investigated these properties in two visualization experiments. The results show that available sources of 3D structural information were sufficient for our subjects to make fast and accurate judgments. Some implications for visualization are discussed.

  • 15. Hast, A
    et al.
    Wesslén, Daniel
    Seipel, Stefan
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Automatic control. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis. Människa-datorinteraktion.
    Improved Diffuse Anisotropic Shading2004In: Sigrad Conference 2004, 2004, p. 57-58Conference paper (Other scientific)
  • 16.
    Hast, Anders
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Jenke, Peter
    University of Gävle.
    Seipel, Stefan
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Shortest Diagonal Triangulation of Convex Layers2013In: The IASTED International Conference on Signal Processing, Pattern Recognition and Applications., 2013, p. 1-7Conference paper (Refereed)
  • 17. Jansen, N
    et al.
    Nejdl, W
    Olbrich, S
    Seipel, S
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology. Interfaculty Units, Centre for Image Analysis. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Automatic control. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    CoVASE: Collaborative Visualization for Constructivist Learning2003In: Proceedings of CSCL Conf. 2003, 2003, p. 249-253Conference paper (Other (popular scientific, debate etc.))
  • 18. Jensen, N
    et al.
    Seipel, Stefan
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Automatic control. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis. Människa-datorinteraktion.
    von Voigt, S
    Raasch, S
    Olbrich, S
    Nejdl, W
    Development of a Virtual Laboratory System for Science Education and the Study of Collaborative Action2004In: AACE ED Media Conference 2004, 2004, p. 21-26Conference paper (Refereed)
  • 19.
    Kjellin, Andreas
    et al.
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Informatics and Media, Human-Computer Interaction.
    Winkler Pettersson, Lars
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Human-Computer Interaction.
    Seipel, Stefan
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Lind, Mats
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Informatics and Media, Human-Computer Interaction.
    Different levels of 3D: An evaluation of visualized discrete spatiotemporal data in space-time cubes2010In: Information Visualization, ISSN 1473-8716, E-ISSN 1473-8724, Vol. 9, no 2, p. 152-164Article in journal (Refereed)
  • 20.
    Kjellin, Andreas
    et al.
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Informatics and Media, Human-Computer Interaction.
    Winkler Pettersson, Lars
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Human-Computer Interaction.
    Seipel, Stefan
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Lind, Mats
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Informatics and Media, Human-Computer Interaction.
    Evaluating 2D and 3D Visualizations of Spatiotemporal Information2010In: ACM Transactions on Applied Perception, ISSN 1544-3558, Vol. 7, no 3, p. 19:1-23Article in journal (Refereed)
  • 21.
    Koch, S
    et al.
    Uppsala University, Medicinska vetenskapsområdet, Faculty of Medicine, Department of Medical Sciences.
    Wagner, I-V
    Seipel, S
    Schneider, W
    Humanistisk-samhällsvetenskapliga vetenskapsområdet, Faculty of Social Sciences, Department of Information Science.
    Computergestütztes Arbeiten und klinisches Dokumentieren am zahnärztlichen Arbeitsplatz (Teil 2): Qualitätssicherung in der digitalen intraoralen Radiographie - Methoden für die Praxis1996In: ZWR, Vol. 1/2, p. 61-64Article in journal (Other scientific)
  • 22.
    Koch, S
    et al.
    Uppsala University, Medicinska vetenskapsområdet, Faculty of Medicine, Department of Medical Sciences.
    Wagner, I-V
    Seipel, S
    Schneider, W
    Humanistisk-samhällsvetenskapliga vetenskapsområdet, Faculty of Social Sciences, Department of Information Science.
    Controlled Improvement and Assessment of Digital Intraoral Radiographs for Quality Assurance in Oral Health Care1996In: Computational Medicine, Public Health and Biotechnology: Building a Man in the Machine - Part 2, World Scientific Series in Mathematical Biology and Medicine, 1996, p. 677-686Chapter in book (Refereed)
  • 23.
    Koch, S
    et al.
    Uppsala University, Medicinska vetenskapsområdet, Faculty of Medicine, Department of Medical Sciences.
    Wagner, I-V
    Seipel, S
    Schneider, W
    Humanistisk-samhällsvetenskapliga vetenskapsområdet, Faculty of Social Sciences, Department of Information Science.
    Knowledge-based diagnosis-oriented improvement of automatically segmented intraoral radiographs1996Conference paper (Refereed)
  • 24. Lim, Nancy Joy
    et al.
    Brandt, S. Anders
    Seipel, Stefan
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Visualisation and evaluation of flood uncertainties based on ensemble modelling2016In: International Journal of Geographical Information Science, ISSN 1365-8816, E-ISSN 1365-8824, Vol. 30, no 2, p. 240-262Article in journal (Refereed)
    Abstract [en]

    This study evaluates how users incorporate visualisation of flood uncertainty information in decision-making. An experiment was conducted where participants were given the task to decide building locations, taking into account homeowners’ preferences as well as dilemmas imposed by flood risks at the site. Two general types of visualisations for presenting uncertainties from ensemble modelling were evaluated: (1) uncertainty maps, which used aggregated ensemble results; and (2) performance bars showing all individual simulation outputs from the ensemble. Both were supplemented with either two-dimensional (2D) or three-dimensional (3D) contextual information, to give an overview of the area.The results showed that the type of uncertainty visualisation was highly influential on users’ decisions, whereas the representation of the contextual information (2D or 3D) was not. Visualisation with performance bars was more intuitive and effective for the task performed than the uncertainty map. It clearly affected users’ decisions in avoiding certain-to-be-flooded areas. Patterns to which the distances were decided from the homeowners’ preferred positions and the uncertainties were similar, when the 2D and 3D map models were used side by side with the uncertainty map. On the other hand, contextual information affected the time to solve the task. With the 3D map, it took the participants longer time to decide the locations, compared with the other combinations using the 2D model.Designing the visualisation so as to provide more detailed information made respondents avoid dangerous decisions. This has also led to less variation in their overall responses.

  • 25.
    Lim, Nancy Joy
    et al.
    Högskolan i Gävle.
    Seipel, Stefan
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Geovisualization of Uncertainty in Simulated Flood Maps2014In: Proceedings of the IADIS conference in Computer Graphics, Visualization, Computer Vision and Image Processing (CGCVIP), 2014, p. 206-214Conference paper (Refereed)
  • 26.
    Lind, Mats
    et al.
    Uppsala University, Humanistisk-samhällsvetenskapliga vetenskapsområdet, Faculty of Social Sciences, Department of Information Science. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Human-Computer Interaction.
    Seipel, Stefan
    Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Human-Computer Interaction.
    Mattiason, Christer
    Displaying meta-information in context2001In: Behaviour and Information Technology, ISSN 0144-929, Vol. 20, no 6, p. 427-432(6)Article in journal (Refereed)
  • 27. Lindkvist, Mikael
    et al.
    Seipel, Stefan
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology. Interfaculty Units, Centre for Image Analysis. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Human-Computer Interaction. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis. Människa-datorinteraktion.
    Methods and application of interactive 3D computer graphics in antropology: Technical Report 2002-002, Dept of Information Technology2002Report (Other (popular scientific, debate etc.))
  • 28.
    Lingfors, David
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Solid State Physics.
    Widén, Joakim
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Solid State Physics.
    Seipel, Stefan
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Interactive visual simulation for photovoltaic design and planning in the built environment2013Conference paper (Other academic)
  • 29.
    Liu, Fei
    et al.
    Högskolan i Gävle.
    Jonsson, Torsten
    Högskolan i Gävle.
    Seipel, Stefan
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Högskolan i Gävle.
    Evaluation of Augmented Reality-Based Building Diagnostics Using Third Person Perspective2020In: ISPRS International Journal of Geo-Information, ISSN 2220-9964, Vol. 9, no 1, article id 53Article in journal (Refereed)
    Abstract [en]

    Comprehensive user evaluations of outdoor augmented reality (AR) applications in the architecture, engineering, construction and facilities management (AEC/FM) industry are rarely reported in the literature. This paper presents an AR prototype system for infrared thermographic façade inspection and its evaluation. The system employs markerless tracking based on image registration using natural features and a third person perspective (TPP) augmented view displayed on a hand-held smart device. We focus on evaluating the system in user experiments with the task of designating positions of heat spots on an actual façade as if acquired through thermographic inspection. User and system performance were both assessed with respect to target designation errors. The main findings of this study show that positioning accuracy using this system is adequate for objects of the size of one decimeter. After ruling out the system inherent errors, which mainly stem from our application-specific image registration procedure, we find that errors due to a human’s limited visual-motoric and cognitive performance, which have a more general implication for using TPP AR for target designation, are only a few centimeters.

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  • 30.
    Liu, Fei
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Seipel, Stefan
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Detection of Façade Regions in Street View Images from Split-and-Merge of Perspective Patches2014In: Journal of Image and Graphics, ISSN 2301-3699, Vol. 2, no 1, p. 8-14Article in journal (Refereed)
    Abstract [en]

    Identification of building façades from digital images is one of the central problems in mobile augmented reality (MAR) applications in the built environment. Directly analyzing the whole image can increase the difficulty of façade identification due to the presence of image portions which are not façade. This paper presents an automatic approach to façade region detection given a single street view image as a pre-processing step to subsequent steps of façade identification. We devise a coarse façade region detection method based on the observation that façades are image regions with repetitive patterns containing a large amount of vertical and horizontal line segments. Firstly, scan lines are constructed from vanishing points and center points of image line segments. Hue profiles along these lines are then analyzed and used to decompose the image into rectilinear patches with similar repetitive patterns. Finally, patches are merged into larger coherent regions and the main building façade region is chosen based on the occurrence of horizontal and vertical line segments within each of the merged regions. A validation of our method showed that on average façade regions are detected in conformity with manually segmented images as ground truth.

  • 31.
    Liu, Fei
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Högskolan i Gävle.
    Seipel, Stefan
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Infrared-visible image registration for augmented reality-based thermographic building diagnostics2015In: Visualization in Engineering, ISSN 2213-7459, Vol. 3, p. 16:1-15, article id 16Article in journal (Refereed)
    Abstract [en]

    Background

    In virtue of their capability to measure temperature, thermal infrared cameras have been widely used in building diagnostics for detecting heat loss, air leakage, water damage etc. However, the lack of visual details in thermal infrared images makes the complement of visible images a necessity. Therefore, it is often useful to register images of these two modalities for further inspection of architectures. Augmented reality (AR) technology, which supplements the real world with virtual objects, offers an ideal tool for presenting the combined results of thermal infrared and visible images. This paper addresses the problem of registering thermal infrared and visible façade images, which is essential towards developing an AR-based building diagnostics application.

    Methods

    A novel quadrilateral feature is devised for this task, which models the shapes of commonly present façade elements, such as windows. The features result from grouping edge line segments with the help of image perspective information, namely, vanishing points. Our method adopts a forward selection algorithm to determine feature correspondences needed for estimating the transformation model. During the formation of the feature correspondence set, the correctness of selected feature correspondences at each step is verified by the quality of the resulting registration, which is based on the ratio of areas between the transformed features and the reference features.

    Results and conclusions

    Quantitative evaluation of our method shows that registration errors are lower than errors reported in similar studies and registration performance is usable for most tasks in thermographic inspection of building façades.

  • 32.
    Liu, Fei
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Univ Gavle, Dept Ind Dev IT & Land Management, S-80176 Gavle, Sweden.
    Seipel, Stefan
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Univ Gavle, Dept Ind Dev IT & Land Management, S-80176 Gavle, Sweden.
    On the precision of third person perspective augmented reality for target designation tasks2017In: Multimedia tools and applications, ISSN 1380-7501, E-ISSN 1573-7721, Vol. 76, no 14, p. 15279-15296Article in journal (Refereed)
    Abstract [en]

    The availability of powerful consumer-level smart devices and off-the-shelf software frameworks has tremendously popularized augmented reality (AR) applications. However, since the built-in cameras typically have rather limited field of view, it is usually preferable to position AR tools built upon these devices at a distance when large objects need to be tracked for augmentation. This arrangement makes it difficult or even impossible to physically interact with the augmented object. One solution is to adopt third person perspective (TPP) with which the smart device shows in real time the object to be interacted with, the AR information and the user herself, all captured by a remote camera. Through mental transformation between the user-centric coordinate space and the coordinate system of the remote camera, the user can directly interact with objects in the real world. To evaluate user performance under this cognitively demanding situation, we developed such an experimental TPP AR system and conducted experiments which required subjects to make markings on a whiteboard according to virtual marks displayed by the AR system. The same markings were also made manually with a ruler. We measured the precision of the markings as well as the time to accomplish the task. Our results show that although the AR approach was on average around half a centimeter less precise than the manual measurement, it was approximately three times as fast as the manual counterpart. Additionally, we also found that subjects could quickly adapt to the mental transformation between the two coordinate systems.

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  • 33.
    Liu, Fei
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Department of Industrial Development, IT and Land Management, University of Gävle.
    Seipel, Stefan
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Department of Industrial Development, IT and Land Management, University of Gävle.
    Precision study on augmented reality-based visual guidance for facility management tasks2018In: Automation in Construction, ISSN 0926-5805, E-ISSN 1872-7891, Vol. 90, p. 79-90Article in journal (Refereed)
  • 34.
    Ma, Lei
    et al.
    Univ Gävle, Fac Engn & Sustainable Dev, Dept Comp & Geospatial Sci, Gävle, Sweden.;Högskolan i Gävle, S-80176 Gävle, Sweden..
    Brandt, Sven Anders
    Univ Gävle, Fac Engn & Sustainable Dev, Dept Comp & Geospatial Sci, Gävle, Sweden..
    Seipel, Stefan
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division Vi3. Univ Gävle, Fac Engn & Sustainable Dev, Dept Comp & Geospatial Sci, Gävle, Sweden.
    Ma, Ding
    Shenzhen Univ, Res Inst Smart Cities, Sch Architecture & Urban Planning, Shenzhen, Peoples R China..
    Simple agents - complex emergent path systems: Agent-based modelling of pedestrian movement2024In: Environment and planning B: Urban analytics and city science, ISSN 2399-8083, Vol. 51, no 2, p. 479-495Article in journal (Refereed)
    Abstract [en]

    In well-planned open and semi-open urban areas, it is common to observe desire paths on the ground, which shows how pedestrians themselves enhance the walkability and affordance of road systems. To better understand how these paths are formed, we present an agent-based modelling approach that simulates real pedestrian movement to generate complex path systems. By using heterogeneous ground affordance and visit frequency of hotspots as environmental settings and by modelling pedestrians as agents, path systems emerge from collective interactions between agents and their environment. Our model employs two visual parameters, angle and depth of vision, and two guiding principles, global conception and local adaptation. To examine the model’s visual parameters and their effects on the cost-efficiency of the emergent path systems, we conducted a randomly generated simulation and validated the model using desire paths observed in real scenarios. The results show that (1) the angle (found to be limited to a narrow range of 90–120°) has a more significant impact on path patterns than the depth of vision, which aligns with Space Syntax theories that also emphasize the importance of angle for modelling pedestrian movement; (2) the depth of vision is closely related to the scale-invariance of path patterns on different map scales; and (3) the angle has a negative exponential correlation with path efficiency and a positive correlation with path costs. Our proposed model can help urban planners predict or generate cost-efficient path installations in well- and poorly designed urban areas and may inspire further approaches rooted in generative science for future cities.

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  • 35.
    Ma, Lei
    et al.
    Univ Gävle, Fac Engn & Sustainable Dev, Dept Comp & Geospatial Sci, S-80176 Gävle, Sweden..
    Seipel, Stefan
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Univ Gävle, Fac Engn & Sustainable Dev, Dept Comp & Geospatial Sci, S-80176 Gävle, Sweden..
    Brandt, Sven Anders
    Univ Gävle, Fac Engn & Sustainable Dev, Dept Comp & Geospatial Sci, S-80176 Gävle, Sweden..
    Ma, Ding
    Shenzhen Univ, Sch Architecture & Urban Planning, Res Inst Smart Cities, Shenzhen 518060, Peoples R China..
    A New Graph-Based Fractality Index to Characterize Complexity of Urban Form2022In: ISPRS International Journal of Geo-Information, ISSN 2220-9964, Vol. 11, no 5, article id 287Article in journal (Refereed)
    Abstract [en]

    Examining the complexity of urban form may help to understand human behavior in urban spaces, thereby improving the conditions for sustainable design of future cities. Metrics, such as fractal dimension, ht-index, and cumulative rate of growth (CRG) index have been proposed to measure this complexity. However, as these indicators are statistical rather than spatial, they result in an inability to characterize the spatial complexity of urban forms, such as building footprints. To overcome this problem, this paper proposes a graph-based fractality index (GFI), which is based on a hybrid of fractal theory and deep learning techniques. First, to quantify the spatial complexity, several fractal variants were synthesized to train a deep graph convolutional neural network. Next, building footprints in London were used to test the method, where the results showed that the proposed framework performed better than the traditional indices, i.e., the index is capable of differentiating complex patterns. Another advantage is that it seems to assure that the trained deep learning is objective and not affected by potential biases in empirically selected training datasets Furthermore, the possibility to connect fractal theory and deep learning techniques on complexity issues opens up new possibilities for data-driven GIS science.

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  • 36. Milutinovic, Goran
    et al.
    Ahonen-Jonnarth, Ulla
    Seipel, Stefan
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology. Faculty of Engineering and Sustainable Development, University of Gävle, Gävle, Sweden.
    Does visual saliency affect decision-making?2021In: Journal of Visualization, ISSN 1343-8875, E-ISSN 1875-8975, Vol. 24, no 6, p. 1267-1285Article in journal (Refereed)
    Abstract [en]

    In the present study, we explore potential effects of visual saliency on decision quality in context of multi-criteria decision-making (MCDM). We compare two visualization techniques: parallel coordinates (PC) and scatterplot matrices (SPM). We investigate the impact of saliency facilitated by means of either color or size. The saliency and visualization techniques were factors in our analysis, and effects were evaluated in terms of decision quality, attention, time on task, and confidence. Results show that the quality of choice and attention were comparable for all saliency conditions when SPM was used. For PC, we found a positive effect of color saliency both on the quality of choice and on attention. Different forms of saliency led to varying times on task in both PC and SPM; however, those variations were not significant. A comparison of PC and SPM shows, users spent less time on the task, obtained better decision quality, and were more confident with their decision when using PC. To summarize, our findings suggest that saliency can increase attention and decision quality in MCDM for certain visualization techniques and forms of saliency. Another contribution of this work is the novel suggestion of the method to elicit of users’ preferences; its potential benefits are discussed in the end of the paper.

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  • 37.
    Milutinovic, Goran
    et al.
    Department of Industrial Development, IT and Land Management, University of Gävle, Gävle, Sweden.
    Ahonen-Jonnarth, Ulla
    Department of Industrial Development, IT and Land Management, University of Gävle, Gävle, Sweden.
    Seipel, Stefan
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Department of Industrial Development, IT and Land Management, University of Gävle, Gävle, Sweden.
    GISwaps: A new method for decision making in continuous choice models based on even swaps2018In: International Journal of Decision Support System Technology, ISSN 1941-6296, E-ISSN 1941-630X, Vol. 10, no 3, p. 57-78Article in journal (Refereed)
    Abstract [en]

    This article describes how continuous GIS-MCDM problems are commonly managed by combining some weighting method based on pairwise comparisons of criteria with an aggregation method. The reliability of this approach may be questioned, though. First, assigning weights to criteria, without taking into consideration the actual consequences or values of the alternatives, is in itself controversial. Second, the value functions obtained by this approach are in most cases linear, which is seldom the case in reality. The authors present a new method for GIS-MCDM in continuous choice models based on Even Swaps. The method is intuitive and easy to use, based on value trade-offs, and thus not relying on criteria weighting. Value functions obtained when using the method may be linear or non-linear, and thereby are more sensitive to the characteristics of the decision space. The performed case study showed promising results regarding the reliability of the method in GIS-MCDM context.

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  • 38. Milutinovic, Goran
    et al.
    Ahonen-Jonnarth, Ulla
    Seipel, Stefan
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Brandt, Sven Anders
    The impact of interactive visualization on trade-off-based geospatial decision-making2019In: International Journal of Geographical Information Science, ISSN 1365-8816, E-ISSN 1365-8824, Vol. 33, no 10, p. 2094-2123Article in journal (Refereed)
  • 39. Milutinovic, Goran
    et al.
    Seipel, Stefan
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. University of Gävle .
    Visual GISwaps: an interactive visualization framework for geospatial decision making2018In: Proc. 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications: Volume 3, SciTePress, 2018, p. 236-243Conference paper (Refereed)
    Abstract [en]

    Different visualization techniques are frequently used in geospatial information systems (GIS) to support geospatial decision making. However, visualization in GIS context is usually limited to the initial phase of the decision-making process, i.e. situation analysis and problem recognition. This is partly due to the choice of methods used in GIS multi-criteria decision-making (GIS-MCDM) that usually deploy some non-interactive approach, leaving the decision maker little or no control over the calculation of overall values for the considered alternatives; the role of visualization is thus reduced to presenting the final results of the computations. The contributions of this paper are twofold. First, we introduce GISwaps, a novel, intuitive interactive method for decision making in geospatial context. The second and main contribution is an interactive visualization of the choice phase of the decision making process. The visualization allows the decision maker to explore the consequenc es of trade-offs and costs accepted during the iterative decision process, both in terms of the abstract relation between different decision variables and in spatial context.

  • 40.
    Milutinovic, Goran
    et al.
    Univ Gävle, Fac Engn & Sustainable Dev, S-80176 Gävle, Sweden..
    Seipel, Stefan
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Univ Gävle, Fac Engn & Sustainable Dev, S-80176 Gävle, Sweden..
    Ahonen-Jonnarth, Ulla
    Univ Gävle, Fac Engn & Sustainable Dev, S-80176 Gävle, Sweden..
    Geospatial Decision-Making Framework Based on the Concept of Satisficing2021In: ISPRS International Journal of Geo-Information, ISSN 2220-9964, Vol. 10, no 5, article id 326Article in journal (Refereed)
    Abstract [en]

    Decision-making methods used in geospatial decision making are computationally complex prescriptive methods, the details of which are rarely transparent to the decision maker. However, having a deep understanding of the details and mechanisms of the applied method is a prerequisite for the efficient use thereof. In this paper, we present a novel decision-making framework that emanates from the need for intuitive and easy-to-use decision support systems for geospatial multi-criteria decision making. The framework consists of two parts: the decision-making model Even Swaps on Reduced Data Sets (ESRDS), and the interactive visualization framework. The decision-making model is based on the concept of satisficing, and as such, it is intuitive and easy to understand and apply. It integrates even swaps, a prescriptive decision-making method, with the findings of behavioural decision-making theories. Providing visual feedback and interaction opportunities throughout the decision-making process, the interactive visualization part of the framework helps the decision maker gain better insight into the decision space and attribute dependencies. Furthermore, it provides the means to analyse and compare the outcomes of different scenarios and decision paths.

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  • 41. Ohlsson, P
    et al.
    Seipel, Stefan
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology. Interfaculty Units, Centre for Image Analysis. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Automatic control. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis. Människa-datorinteraktion.
    Real-time Rendering of Accumulated Snow2004In: Sigrad Conference 2004, 2004, p. 25-32Conference paper (Refereed)
  • 42.
    Olsson, Eva
    et al.
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Human-Computer Interaction. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis. Människa-datorinteraktion.
    Seipel, Stefan
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology. Interfaculty Units, Centre for Image Analysis. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Human-Computer Interaction. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis. Människa-datorinteraktion.
    Jansson, Anders
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Human-Computer Interaction. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis. Människa-datorinteraktion.
    Sandblad, Bengt
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Human-Computer Interaction. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis. Människa-datorinteraktion.
    The Windscreen Used as a Display for Navigation Information, An Introductory Study: Technical Report 2002-017, Dept. of Information Technology2002Report (Other (popular scientific, debate etc.))
  • 43.
    Pettersson, Lars W
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Human-Computer Interaction.
    Jensen, N
    Seipel, Stefan
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Human-Computer Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    A Virtual laboratory for Computer Graphics Education2003In: Proceedings of EUROGRAPHICS Conf. 2003, 2003Conference paper (Refereed)
  • 44.
    Pettersson, Lars W
    et al.
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Human-Computer Interaction. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis. Människa-datorinteraktion.
    Lind, Mats
    Humanistisk-samhällsvetenskapliga vetenskapsområdet, Faculty of Social Sciences, Department of Information Science. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Human-Computer Interaction. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Spak, U
    Seipel, Stefan
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology. Interfaculty Units, Centre for Image Analysis. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Human-Computer Interaction. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis. Människa-datorinteraktion.
    Visualizations of symbols in a horizontal multiple viewer 3D display environment2005In: IEEE Proceedings of the 9th International Conference on Information Visualization, 2005, p. 357-362Conference paper (Refereed)
  • 45.
    Pettersson, Lars Winkler
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Human-Computer Interaction.
    Seipel, Stefan
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Human-Computer Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Spak, Ulrik
    Collaborative 3D Vizualizations of Geo-Spatial Information for Command and Control2004In: Sigrad 2004, 2004, p. 41-47Conference paper (Refereed)
  • 46.
    Pettersson, Lars Winkler
    et al.
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Human-Computer Interaction. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis. Människa-datorinteraktion.
    Seipel, Stefan
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology. Interfaculty Units, Centre for Image Analysis. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Human-Computer Interaction. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis. Människa-datorinteraktion.
    Wesslén, Daniel
    In situ tomographic display for interactive data vizualization2004In: NordiCHI 2004, 2004Conference paper (Refereed)
  • 47. Ren, Zheng
    et al.
    Jiang, Bin
    Seipel, Stefan
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Capturing and characterizing human activities using building locations in America2019In: ISPRS International Journal of Geo-Information, ISSN 2220-9964, Vol. 8, no 5, article id 200Article in journal (Refereed)
  • 48.
    Ren, Zheng
    et al.
    Univ Gävle, Fac Engn & Sustainable Dev, Gävle, Sweden..
    Seipel, Stefan
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division Vi3. Univ Gävle, Fac Engn & Sustainable Dev, Gävle, Sweden..
    Jiang, Bin
    Univ Gävle, Fac Engn & Sustainable Dev, Gävle, Sweden.;Hong Kong Univ Sci & Technol Guangzhou, Urban Governance & Design Thrust, Soc Hub, Guangzhou, Peoples R China..
    A topology-based approach to identifying urban centers in America using multi-source geospatial big data2024In: Computers, Environment and Urban Systems, ISSN 0198-9715, E-ISSN 1873-7587, Vol. 107, article id 102045Article in journal (Refereed)
    Abstract [en]

    Urban structure can be better comprehended through analyzing its cores. Geospatial big data facilitate the identification of urban centers in terms of high accuracy and accessibility. However, previous studies seldom leverage multi-source geospatial big data to identify urban centers from a topological perspective. This study attempts to identify urban centers through the spatial integration of multi-source geospatial big data, including nighttime light imagery (NTL), building footprints (BFP) and street nodes of OpenStreetMap (OSM). We use a novel topological approach to construct complex networks from intra-urban hotspots based on the theory of centers by Christopher Alexander. We compute the degree of wholeness value for each hotspot as the centric index. The overlapped hotspots with the highest centric indices are regarded as urban centers. The identified urban centers in New York, Los Angeles, and Houston are consistent with their downtown areas, with overall accuracy of 90.23%. In Chicago, a new urban center is identified considering a larger spatial extent. The proposed approach can effectively and objectively prevent counting those hotspots with high intensity values but few neighbors into the result. This study proposes a topological approach for urban center identification and a bottom-up perspective for sustainable urban design.

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  • 49. Seffers, Gaëlle
    et al.
    Åhlén, Juia
    Seipel, Stefan
    Ooms, Kristien
    Assessing Damage – Can the Crowd Interpret Colour and 3D Information?2021In: Cartographic Journal, ISSN 0008-7041, E-ISSN 1743-2774, Vol. 58, p. 69-82Article in journal (Refereed)
    Abstract [en]

    The goal of this study is to investigate how efficiently and effectively collapsed buildings – due to the occurrence of a disaster – can be localized by a general crowd. Two types of visualization parameters are evaluated in an online user study: (1) greyscale images (indicating height information) versus true colours; (2) variation in the vertical viewing angle (0°, 30° and 60°). Additionally, the influence of map use expertise on how the visualizations are interpreted, is investigated. The results indicate that the use of the greyscale image helps to locate collapsed buildings in an efficient and effective manner. The use of the viewing angle of 60° is the least appropriate. A person with a map use expertise will prefer the greyscale image over the colour image. To confirm the benefits of the use of three-dimensional visualizations and the use of the colour image, more research is needed.

  • 50.
    Seipel, S
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Human-Computer Interaction. HUMAN-COMPUTER INTERACTION.
    Information Visualization using Transparent Shape Impostors2003In: Proc. EUROGRAPHICS Conference 2003, Short Presentations, 2003Conference paper (Refereed)
12 1 - 50 of 79
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