15 November 2007 Motion estimation and geometric active contours for object tracking
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Proceedings Volume 6786, MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition; 678625 (2007) https://doi.org/10.1117/12.749411
Event: International Symposium on Multispectral Image Processing and Pattern Recognition, 2007, Wuhan, China
Abstract
We present a robust geometric active contour model to track targets in video sequences captured from mobile cameras. The target's contour is tracked on each frame of the sequence by regional information. The regional information is calculated by color histogram. The matching criterion is formulated by minimizing the Bhattacharyya coefficient between the color histogram of reference target and that of the background. The contour's evolution is implemented using the geometric active contour algorithm and the level set method. For each frame coming from the sequence, motion estimation is done before the contour evolution process. To make so, Kalman prediction and template matching are performed as the motion estimation technique to locate the region of interest (ROI). The robustness and effectiveness of the proposed algorithm is demonstrated on real sequences.
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
You Li, "Motion estimation and geometric active contours for object tracking", Proc. SPIE 6786, MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition, 678625 (15 November 2007); doi: 10.1117/12.749411; https://doi.org/10.1117/12.749411
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