An improved watershed algorithm based on efficient computation of shortest paths
Pattern Recognition
Speeded-Up Robust Features (SURF)
Computer Vision and Image Understanding
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Motion analysis plays a key role in the understanding of video imagery. The goal of our research is simultaneous camera motion modeling and object motion tracking in video sequences captured with public access pan-tilt-zoom web cameras. As a first step, we have developed and evaluated two techniques for camera motion modeling. Our first method uses SURF feature detection to detect camera and object motion. Our second method uses watershed region segmentation on sequential video frames, followed by template matching to detect the motion of watershed region over time and quantify camera motion.