Incremental recognition of traffic situations from video image sequences

Abstract Our image evaluation system XTRACK tracks multiple-vehicle-configurations in image sequences. The resulting geometric state descriptions are associated with fuzzy attributes and relations and thereby form the basis for incremental characterization of traffic situations from the point of view of selected road users or observers. Knowledge representation and inference is performed by means of fuzzy metric temporal logic in order to provide an in-depth analyzable transition from raw video data to conceptual descriptions of traffic situations.

[1]  M. Teal,et al.  Spatial-Temporal Reasoning Based on Object Motion , 1996, BMVC.

[2]  Hans-Hellmut Nagel,et al.  Integration of Image Sequence Evaluation and Fuzzy Metric Temporal Logic Programming , 1997, KI.

[3]  Hans-Hellmut Nagel,et al.  Ermittlung von begrifflichen Beschreibungen von Geschehen in Straßenverkehrsszenen mit Hilfe unscharfer Mengen , 1993, Informatik - Forschung und Entwicklung.

[4]  Daryl T. Lawton,et al.  Interactive Model-Based Vehicle Tracking , 1996, IEEE Trans. Pattern Anal. Mach. Intell..

[5]  Wolfgang Krüger.  Begriffsgraphen an der Benutzerschnittstelle , 1992 .

[6]  Allan D. Jepson,et al.  The Computational Perception of Scene Dynamics , 1997, Comput. Vis. Image Underst..

[7]  Mubarak Shah,et al.  Motion-based recognition a survey , 1995, Image Vis. Comput..

[8]  Karl Schäfer,et al.  Unscharfe zeitlogische Modellierung von Situationen und Handlungen in Bildfolgenauswertung und Robotik , 1996, DISKI.

[9]  Hans-Hellmut Nagel,et al.  From image sequences towards conceptual descriptions , 1988, Image Vis. Comput..

[10]  H. Kollnig,et al.  The Association of Situation Graphs with Temporal Variations inImage , 1995 .

[11]  Hans-Hellmut Nagel,et al.  Knowledge representation for the generation of quantified natural language descriptions of vehicle traffic in image sequences , 1996, Proceedings of 3rd IEEE International Conference on Image Processing.

[12]  Jitendra Malik,et al.  Combining Multiple Motion Estimates for Vehicle Tracking , 1996 .

[13]  Shaogang Gong,et al.  Visual Surveillance in a Dynamic and Uncertain World , 1995, Artif. Intell..

[14]  SANDY DANCE,et al.  A concurrent, hierarchical approach to symbolic dynamic scene interpretation , 1996, Pattern Recognit..

[15]  Jitendra Malik,et al.  Automatic Symbolic Traffic Scene Analysis Using Belief Networks , 1994, AAAI.

[16]  Geoffrey D. Sullivan,et al.  A Filter for Visual Tracking Based on a Stochastic Model for Driver Behaviour , 1996, ECCV.

[17]  Hans-Hellmut Nagel,et al.  Matching Object Models to Segments from an Optical Flow Field , 1996, ECCV.

[18]  Hans-Hellmut Nagel,et al.  Association of Motion Verbs with Vehicle Movements Extracted from Dense Optical Flow Fields , 1994, ECCV.

[19]  Hans-Hellmut Nagel,et al.  Influence of an Explicitly Modelled 3D Scene on the Tracking of Partially Occluded Vehicles , 1997, Comput. Vis. Image Underst..

[20]  Geoffrey D. Sullivan,et al.  Filter for Car Tracking Based on Acceleration and Steering Angle , 1996, BMVC.

[21]  Zhi-Qiang Liu,et al.  Picture Interpretation: A Symbolic Approach , 1995, Series in Machine Perception and Artificial Intelligence.

[22]  Hans-Hellmut Nagel,et al.  Berechnung natürlichsprachlicher Beschreibungen von Straßenverkehrsszenen aus Bildfolgen unter Verwendung von Geschehens- und Verdeckungsmodellierungen , 1996, DAGM-Symposium.