Real Time Trajectory Search in Video Summarization using Direct Distance Transform
Searching for human trajectories in a summarized video is a way of analyzing such video within a smaller group of human moving along the same path. We propose a real time novel method for similarity search for human trajectories using a distance transform of each extracted human tunnel. We integrate this method with our previous work, Real Time Tunnel Based Video Summarization using Direct Shift Collision Detection (DSCD), which provides the human tunnels with trajectory information for being analyzed. The algorithm first creates a distance transform from provided trajectory information. A model of trajectory for screening irrelevant tunnels out of the summarized video is then used as a query. An efficient technique as in DSCD is used for calculating a direct distance transform (DDT). Then a similarity between trajectory model and human trajectories are ranked. The advantage of linear time complexity of both DSCD and distance transform gives us a real time search results while more relevant summarization output can be obtained.
component Video summarization Object tracking Tunnel processing HOG Direct Shift Collision Detection Distance Transform Film Map generation Just-in-Time renderer
Nagul Cooharojananone Siriwat Kasamwattanarote Shin’ichi Satoh Rajalida Lipikorn
Department of Mathematics, Faculty of Science, Chulalongkorn University, Bangkok 10330, Thailand National Institute of Informatics 2-1-2 Hitotsubashi, Chiyoda-ku, Tokyo, Japan 101-8430
国际会议
2010 IEEE 10th International Conference on Signal Processing(第十届信号处理国际会议 ICSP 2010)
北京
英文
932-935
2010-08-24（万方平台首次上网日期，不代表论文的发表时间）