Learning the distribution of object trajectories for event recognition
BMVC '95 Proceedings of the 6th British conference on Machine vision (Vol. 2)
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Automatic Panoramic Image Stitching using Invariant Features
International Journal of Computer Vision
Speeded-Up Robust Features (SURF)
Computer Vision and Image Understanding
Eliminating Ghosting Artifacts for Panoramic Images
ISM '09 Proceedings of the 2009 11th IEEE International Symposium on Multimedia
Unexpected Human Behavior Recognition in Image Sequences Using Multiple Features
ICPR '10 Proceedings of the 2010 20th International Conference on Pattern Recognition
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In this paper, we present a novel method to abnormal behavior detection in PTZ camera networks. To extract motion information of scene in moving camera environment, we use panoramic background which is generated by frames. In contrast with previous methods, we use MRF framework to integrate temporal and spatial information of frames to generate panoramic background. In addition, we introduce a panoramic activity map to detect abnormal behavior of people. The panoramic activity map is useful in various abnormal situation since it includes multiple features such as location, motion, direction and pace of objects. Experimental results from real sequences demonstrate the effectiveness of our method.