Finding long and similar parts of trajectories
Proceedings of the 17th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
Trajectory analysis in natural images using mixtures of vector fields
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Toward visually inferring the underlying causal mechanism in a traffic-light-controlled crossroads
ACIVS'06 Proceedings of the 8th international conference on Advanced Concepts For Intelligent Vision Systems
NNCluster: an efficient clustering algorithm for road network trajectories
DASFAA'10 Proceedings of the 15th international conference on Database Systems for Advanced Applications - Volume Part II
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Activity analysis and semantic interpretation of tracked targets in a dynamic image sequence has recently attracted more attentions in computer vision. In this paper, a framework for semantic interpretation of vehicle and pedestrian's behaviors is proposed for practical applications in visual traffic surveillance. The trajectories recorded in the visual tracking process are analyzed using dynamic clustering and classification on which high level semantic interpretation is based. Experimental results are presented to illustrate the performance of the proposed algorithm.