Human specific activity retrieval from a surveillance image sequence

We propose an image processing system which searches the moving human and vehicles from the long-term surveillance video for intruder detection or parking lot monitoring, by comparing a series of retrieval queries like passing a certain area, moving direction, duration time and so on. In such a system, not only on-line detection from real-time video by pre-defined query but also quick re-search going back to the past when the user changed the query, and post-retrieval by interactive query change are required. In proposed method, we simplified the image retrieval meta-data to be described in a small and fixed length data however complicated the trajectory of moving object is. Moreover, the matching core function of image retrieval process is realized by a simple comparator. That enables fast image retrieval however complicated the series of the retrieval queries is.

[1]  Fatih Porikli,et al.  Human Body Tracking by Adaptive Background Models and Mean-Shift Analysis , 2003 .

[2]  Manabu Hashimoto Technologies of Video Security for Safe and Relieved Society( Intelligent Sensing for Comfortable and Safe Environments) , 2006 .

[3]  W. Eric L. Grimson,et al.  Adaptive background mixture models for real-time tracking , 1999, Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149).

[4]  Yasushi Yagi,et al.  Human detection in outdoor scene using spatio-temporal motion analysis , 2004, Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004..

[5]  Dorin Comaniciu,et al.  Real-time tracking of non-rigid objects using mean shift , 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).