Proceedings of the third ACM international workshop on Video surveillance & sensor networks
On-line trajectory clustering for anomalous events detection
Pattern Recognition Letters
On-line trajectory clustering for anomalous events detection
Pattern Recognition Letters - Special issue on vision for crime detection and prevention
Learning People Trajectories Using Semi-directional Statistics
AVSS '09 Proceedings of the 2009 Sixth IEEE International Conference on Advanced Video and Signal Based Surveillance
International Journal of Robotics Research
Incremental learning of statistical motion patterns with growing hidden Markov models
IEEE Transactions on Intelligent Transportation Systems
Clustering of vehicle trajectories
IEEE Transactions on Intelligent Transportation Systems
Trajectory-based representation of human actions
ICMI'06/IJCAI'07 Proceedings of the ICMI 2006 and IJCAI 2007 international conference on Artifical intelligence for human computing
Behavior pattern extraction by trajectory analysis
Frontiers of Computer Science in China
Clustering of trajectories in video surveillance using growing neural gas
IWINAC'11 Proceedings of the 4th international conference on Interplay between natural and artificial computation - Volume Part I
Motion segmentation by model-based clustering of incomplete trajectories
ECML PKDD'11 Proceedings of the 2011 European conference on Machine learning and knowledge discovery in databases - Volume Part II
Online clustering of high-dimensional trajectories under concept drift
ECML PKDD'11 Proceedings of the 2011 European conference on Machine learning and knowledge discovery in databases - Volume Part II
Mining paths of complex crowd scenes
ISVC'05 Proceedings of the First international conference on Advances in Visual Computing
A novel trajectory clustering approach for motion segmentation
MMM'10 Proceedings of the 16th international conference on Advances in Multimedia Modeling
A novel framework for motion segmentation and tracking by clustering incomplete trajectories
Computer Vision and Image Understanding
On the use of a minimal path approach for target trajectory analysis
Pattern Recognition
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A system is described that tracks moving objects in a video dataset so as to extract a representation of the objects' 3D trajectories. The system then finds hierarchical clusters of similar trajectories in the video dataset. Objects' motion trajectories are extracted via an EKF formulation that provides each object's 3D trajectory up to a constant factor. To increase accuracy when occlusions occur, multiple tracking hypotheses are followed. For trajectory-based clustering and retrieval, a modified version of edit distance, called longest common subsequence is employed. Similarities are computed between projections of trajectories on coordinate axes. Trajectories are grouped based, using an agglomerative clustering algorithm. To check the validity of the approach, experiments using real data were performed.