Title :
Extraction and clustering of motion trajectories in video
Author :
Buzan, Dan ; Sclaroff, Stan ; Kollios, George
Author_Institution :
Boston Univ., MA, USA
Abstract :
A system that tracks moving objects in a video dataset so as to extract a representation of the objects´ 3D trajectories is described. 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.
Keywords :
image motion analysis; image retrieval; pattern clustering; video signal processing; EKF formulation; agglomerative clustering algorithm; edit distance; longest common subsequence; motion trajectories extraction; moving object tracking; multiple tracking hypotheses; trajectory-based clustering; video dataset; Clustering algorithms; Discrete Fourier transforms; Motion estimation; Object detection; Optical filters; Remote monitoring; Surveillance; Tracking; Trajectory; Video sequences;
Conference_Titel :
Pattern Recognition, 2004. ICPR 2004. Proceedings of the 17th International Conference on
Print_ISBN :
0-7695-2128-2
DOI :
10.1109/ICPR.2004.1334287