Iconic indexing by 2-D strings
IEEE Transactions on Pattern Analysis and Machine Intelligence
Maintaining knowledge about temporal intervals
Communications of the ACM
Modeling of Moving Objects in a Video Database
ICMCS '97 Proceedings of the 1997 International Conference on Multimedia Computing and Systems
Using object and trajectory analysis to facilitate indexing and retrieval of video
Knowledge-Based Systems
Fast stroke matching by angle quantization
Proceedings of the First International Conference on Immersive Telecommunications
Motion analysis via feature point tracking technology
MMM'11 Proceedings of the 17th international conference on Advances in multimedia modeling - Volume Part II
Measuring similarity in the semantic representation of moving objects in video
KSEM'06 Proceedings of the First international conference on Knowledge Science, Engineering and Management
CIVR'06 Proceedings of the 5th international conference on Image and Video Retrieval
International Journal of Computer Vision
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In this paper, we propose a new spatio-temporal representation scheme using moving objects' trajectories in video data. In order to support content-based retrieval on video data very well, our representation scheme considers the moving distance of an object during a given time interval as well as its temporal and spatial relations. Based on our representation scheme, we present a new similarity measure algorithms for the trajectory of moving objects, which provides ranking for the retrieved video results. Finally, we show from our experiment that our representation scheme achieves about 20% higher precision while holding about the same recall, compared with Li's and Shan's schemes.