Visuelle Analyse von Videoströmen: Institut für Visualisierung und Interaktive Systeme
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Visual Analytics of Video Data

 

 

Scalable Visual Analytics for Video Data” is a project funded by the Deutsche Forschungsgemeinschaft (German Research Foundation) in the context of the priority program “Scalable Visual Analytics: Interactive Visual Analysis Systems of Complex Information Spaces” (1335) and started in the middle of 2008. The project is a collaboration of the Visualization Research Center, Universität Stuttgart and the Intelligent Systems Group of the University of Stuttgart.


A substantial amount of electronic data that is acquired on a regular basis is in the form of video data. A typical example is the continuous data input from closed circuit television (CCTV) cameras. The current practice of directly viewing video footage does not scale well with the amount of video because it permanently requires user attention even for, in most parts, uninteresting video material. The main goal of this project is to support users in the interactive analysis of video data in order to efficiently identify and understand regular and irregular behavior in video recordings. One challenge is that irregular behavior cannot be completely defined beforehand and, therefore, fully automatic computer vision techniques cannot provide a complete analysis. Another challenge is the difficulty of interpreting image data of complex scenarios that is often affected by noise and that contains only partial image information due to occlusion. Our strategy is to combine partially automatic image analysis with visualization and interaction: in this way, ambiguities and uncertainties in computer-based video analysis can be resolved by the human users with their excellent capabilities of interpreting image data and identifying structure. By integrating the applicants’ expertise in computer vision, visualization, perception oriented graphics, and interactive systems, this project has the goal of a scalable visual analytics tool for video which allows for video analysis on various levels of abstraction and which supports single camera and multiple camera CCTV setups.

Project publications

2013

Höferlin, Benjamin; Höferlin, Markus; Weiskopf, Daniel; Heidemann, Gunther: Scalable Video Visual Analytics. In: Information Visualization Journal (2013) (Noch nicht erschienen).
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Interactive Schematic Summaries for Faceted Exploration of Surveillance Video
Höferlin, Markus; Höferlin, Benjamin; Heidemann, Gunther; Weiskopf, Daniel: Interactive Schematic Summaries for Faceted Exploration of Surveillance Video. In: IEEE Transactions on Multimedia: Nr. 4 (2013) (Noch nicht erschienen).
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Gesamtanzahl: 2

2012

Borgo, Rita; Chen, Min; Daubney, Ben; Grundy, Edward; Heidemann, Gunther; Höferlin, Benjamin; Höferlin, Markus; Jänicke, Heike; Weiskopf, Daniel; Xie, Xianghu: State of the Art Report on Video-based Graphics and Video Visualizations. In: : Nr. 8 (2012), S. 2450-2477.
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Evaluation of Fast-Forward Video Visualization
Höferlin, Markus; Kurzhals, Kuno; Höferlin, Benjamin; Heidemann, Gunther; Weiskopf, Daniel: Evaluation of Fast-Forward Video Visualization. In: IEEE Transactions on Visualization and Computer Graphics (TVCG): Nr. 12 (2012), S. 2095-2103.
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Auditory Support for Situation Awareness in Video Surveillance
Höferlin, Benjamin; Höferlin, Markus; Goloubets, Boris; Heidemann, Gunther; Weiskopf, Daniel: Auditory Support for Situation Awareness in Video Surveillance. In: In Proceedings of the International Conference on Auditory Display (ICAD) (Noch nicht erschienen).
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Visual Analytics of Mobile Data
Höferlin, Benjamin; Höferlin, Markus; Räuchle, Jürgen: Visual Analytics of Mobile Data. In: Proceedings of the Nokia Mobile Data Challenge 2012 Workshop, 2012.
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Inter-Active Learning of Ad-Hoc Classifiers for Video Visual Analytics
Höferlin, Benjamin; Netzel, Rudolf; Höferlin, Markus; Weiskopf, Daniel; Heidemann, Gunther: Inter-Active Learning of Ad-Hoc Classifiers for Video Visual Analytics. In: IEEE Conference on Visual Analytics Science and Technology (VAST), 2012, S. 23-32, 2012.
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Learning a Visual Attention Model for Adaptive Fast-Forward in Video Surveillance
Höferlin, Benjamin; Pflüger, Hermann; Höferlin, Markus; Heidemann, Gunther; Weiskopf, Daniel: Learning a Visual Attention Model for Adaptive Fast-Forward in Video Surveillance. In: In Proceedings of International Conference on Pattern Recognition Applications and Methods (ICPRAM), S. 25-32, 2012.
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Visual Analytics for Dynamic Evacuation Planning
Reddy, Rajesh; Höferlin, Markus; Dambier, Michael; Weiskopf, Daniel: Visual Analytics for Dynamic Evacuation Planning. In: International Workshop on Visual Analytics (EuroVA), S. 13-17, 2012.
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Gesamtanzahl: 7

2011

Burch, Michael; Heinrich, Julian; Konevtsova, Natalia; Höferlin, Markus; Weiskopf, Daniel: Evaluation of Traditional, Orthogonal, and Radial Tree Diagrams by an Eye Tracking Study. In: IEEE Transactions on Visualization and Computer Graphics: Nr. 6 (2011), S. 2440–2448.
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Information-Based Adaptive Fast-Forward for Visual Surveillance
Höferlin, Benjamin; Höferlin, Markus; Weiskopf, Daniel; Heidemann, Gunther: Information-Based Adaptive Fast-Forward for Visual Surveillance. In: Multimedia Tools and Applications: Nr. 1 (2011), S. 127-150.
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Uncertainty-Aware Video Visual Analytics of Tracked Moving Objects
Höferlin, Markus; Höferlin, Benjamin; Weiskopf, Daniel; Heidemann, Gunther: Uncertainty-Aware Video Visual Analytics of Tracked Moving Objects. In: Journal of Spatial Information Science (JOSIS) (2011), S. 87-117.
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A Survey on Video-based Graphics and Video Visualization
Borgo, Rita; Chen, Min; Daubney, Ben; Grundy, Edward; Jänicke, Heike; Heidemann, Gunther; Höferlin, Benjamin; Höferlin, Markus; Weiskopf, Daniel; Xie, Xianghu: A Survey on Video-based Graphics and Video Visualization. In: EG 2011 - State of the Art Reports, S. 1-23, 2011.
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Evaluation of Background Subtraction Techniques for Video Surveillance
Brutzer, Sebastian; Höferlin, Benjamin; Heidemann, Gunther: Evaluation of Background Subtraction Techniques for Video Surveillance. In: Computer Vision and Pattern Recognition (CVPR), S. 1937-1944, 2011.
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Burch, Michael; Höferlin, Markus; Weiskopf, Daniel: Layered TimeRadarTrees. In: Proceedings of 15th International Conference on Information Visualization (IV), S. 18-25, 2011.
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Visualizing Dynamic Quantitative Data in Hierarchies. TimeEdgeTrees: Attaching Dynamic Weights to Tree Edges
Burch, Michael; Weiskopf, Daniel: Visualizing Dynamic Quantitative Data in Hierarchies. TimeEdgeTrees: Attaching Dynamic Weights to Tree Edges. In: Proceedings of International Conference on Visualization Theory and Applications, S. 177-186, 2011.
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Interactive Auditory Display to Support Situational Awareness in Video Surveillance
Höferlin, Benjamin; Höferlin, Markus; Raschke, Michael; Heidemann, Gunther; Weiskopf, Daniel: Interactive Auditory Display to Support Situational Awareness in Video Surveillance. In: In Proceedings of the International Conference on Auditory Display (ICAD), 2011.
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Interactive Schematic Summaries for Exploration of Surveillance Video
Höferlin, Markus; Höferlin, Benjamin; Weiskopf, Daniel; Heidemann, Gunther: Interactive Schematic Summaries for Exploration of Surveillance Video. In: Proceedings of the ACM International Conference on Multimedia Retrieval (ICMR '11), S. 9:1-9:8, 2011.
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Gesamtanzahl: 9

2010

Selection of an Optimal Set of Discriminative and Robust Local Features with Application to Traffic Sign Recognition
Höferlin, Benjamin; Heidemann, Gunther: Selection of an Optimal Set of Discriminative and Robust Local Features with Application to Traffic Sign Recognition. In: WSCG 2010, 18th International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision (2010), S. 9-16.
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Video Visualization for Snooker Skill Training
Höferlin, Markus; Grundy, Edward; Borgo, Rita; Weiskopf, Daniel; Chen, Min; Griffiths, Iwan W.; Griffiths, Wayne: Video Visualization for Snooker Skill Training. In: Computer Graphics Forum: Nr. 3 (2010), S. 1053-1062.
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Weiskopf, Daniel; Andrienko, Gennady L.; Andrienko, Natalia V.; Bak, Peter: Visuelle Bewegungsanalyse in Video- und Geodaten. In: Informatik Spektrum: Nr. 6 (2010), S. 580-588.
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3D Object Localization via Stereo Vision using an Omnidirectional and a Perspective Camera
Käppeler, Uwe-Philipp; Höferlin, Markus; Levi, Paul: 3D Object Localization via Stereo Vision using an Omnidirectional and a Perspective Camera. In: Proceedings of the 2nd Workshop on Omnidirectional Robot Vision - A Workshop of the 2010 IEEE International Conference on Robotics and Automation (ICRA2010), S. 7-12, 2010.
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Gesamtanzahl: 4

2009

Innovative Filtering Techniques and Customized Analytic Tools
Bosch, Harald; Heinrich, Julian; Müller, Christoph; Höferlin, Benjamin; Reina, Guido; Höferlin, Markus; Wörner, Michael; Koch, Steffen: Innovative Filtering Techniques and Customized Analytic Tools. In: Proc. IEEE Symp. on Visual Analytics Science and Technology, 2009. VAST'09, S. 269-270, 2009.
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Towards Reliable Traffic Sign Recognition
Höferlin, Benjamin; Zimmermann, Klaus: Towards Reliable Traffic Sign Recognition. In: Intelligent Vehicles Symposium 2009 IEEE, S. 324-329, 2009.
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Video Visual Analytics of Tracked Moving Objects
Höferlin, Markus; Höferlin, Benjamin; Weiskopf, Daniel: Video Visual Analytics of Tracked Moving Objects. In: Proceedings of 3rd Workshop on Behaviour Monitoring and Interpretation, S. 59-64, 2009.
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Gesamtanzahl: 3