Tracking and data association
Computing occluding and transparent motions
International Journal of Computer Vision
Performance of optical flow techniques
International Journal of Computer Vision
Direct incremental model-based image motion segmentation for video analysis
Signal Processing - Video segmentation for content-based processing manipulation
Unsupervised video segmentation based on watersheds and temporal tracking
IEEE Transactions on Circuits and Systems for Video Technology
Object recognition and tracking for remote video surveillance
IEEE Transactions on Circuits and Systems for Video Technology
Color-based road sign detection and tracking
ICIAR'07 Proceedings of the 4th international conference on Image Analysis and Recognition
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In this paper an approach for automatic target detection and tracking, using multisensor image sequences with the presence of camera motion is presented. The approach consists of three parts. The first part uses a motion segmentation method for the detection of targets in the visible images sequence. The second part uses a Gaussian background model for detecting objects presented in the infrared sequence, which is preprocessed to eliminate the camera motion. The third part combines the individual results of the detection systems; it extends the Joint Probabilistic Data Association (JPDA) algorithm to handle an arbitrary number of sensors. Our approach is tested using image sequences with high clutter on dynamic environments. Experimental results show that the system detects 99% of the targets in the scene, and the fusion module removes 90% of the false detections.