MODES: moving objects detection and extraction system
ACC'08 Proceedings of the WSEAS International Conference on Applied Computing Conference
AVSS '09 Proceedings of the 2009 Sixth IEEE International Conference on Advanced Video and Signal Based Surveillance
Dynamic Performance Measures for Object Tracking Systems
AVSS '09 Proceedings of the 2009 Sixth IEEE International Conference on Advanced Video and Signal Based Surveillance
Segmentation of motion objects from surveillance video sequences using partial correlation
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Tracking humans using novel optical flow algorithm for surveillance videos
COMPUTE '11 Proceedings of the Fourth Annual ACM Bangalore Conference
| Hi-index | 0.00 |
Person tracking systems are dependent on being able to locate a person accurately across a series of frames. Optical flow can be used to segment a moving object from a scene, provided the expected velocity of the moving object is known; but successful detection also relies on being able segment the background. A problem with existing optical flow techniques is that they don't discriminate the foreground from the background, and so often detect motion (and thus the object) in the background. To overcome this problem, we propose a new optical flow technique, that is based upon an adaptive background segmentation technique, which only determines optical flow in regions of motion. This technique has been developed with a view to being used in surveillance systems, and our testing shows that for this application it is more effective than other standard optical flow techniques.