Shape and motion from image streams under orthography: a factorization method
International Journal of Computer Vision
A multi-body factorization method for motion analysis
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Spatio-temporal video search using the object based video representation
ICIP '97 Proceedings of the 1997 International Conference on Image Processing (ICIP '97) 3-Volume Set-Volume 1 - Volume 1
A probabilistic framework for semi-supervised clustering
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Interactive video exploration using pose slices
ACM SIGGRAPH 2006 Sketches
Video browsing by direct manipulation
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
ICASSP '09 Proceedings of the 2009 IEEE International Conference on Acoustics, Speech and Signal Processing
Clustering Point Trajectories with Various Life-Spans
CVMP '09 Proceedings of the 2009 Conference for Visual Media Production
Tracking and Clustering Salient Features in Image Sequences
CVMP '10 Proceedings of the 2010 Conference on Visual Media Production
Semantic-Based Surveillance Video Retrieval
IEEE Transactions on Image Processing
Motion-based video retrieval by trajectory matching
IEEE Transactions on Circuits and Systems for Video Technology
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Video browsing methods are complementary to search and retrieval approaches, as they allow for exploration of unknown content sets. Objects and their motion convey important semantics of video content, which is relevant information for video browsing. We propose extending an existing video browsing tool in order to support clustering of objects with similar motion and visualization of the objects' positions and trajectories. This requires the automatic extraction of moving objects and estimation of their trajectories, as well as the ability to group objects with similar trajectories. For the first issue we describe the application of a recently proposed motion trajectory clustering algorithm, for the second we use k-medoids clustering and the dynamic time warping distance. We present evaluation results of both steps on real world traffic sequences from the Hopkins155 data set. Finally we describe the description of analysis results using MPEG-7 and the integration into the video browsing tool.