Abstract
In this study, we present a novel multi-cues active contours based method for tracking target contours using edge, region, and shape information. To locate the target position, a contour based meanshift tracker is designed which combines both color and texture information. In order to reduce the adverse impact of sophisticated background and accelerate the curve motion, we extract rough target region from the coming frame by the proposed target appearance model. What’s more, both discriminative pre-learning based global layer and voting based local layer are integrated into our appearance model. For obtaining the detailed target boundaries, we embed edge, region, and shape information into the level sets based multi-cues active contour model (MCAC). Experiments on seven video sequences demonstrate that the proposed method performs better than other competitive contour tracking methods under various tracking environment.
P. Lv—This work is supported by the National Natural Science Foundation of China (No. 61175096 and No. 61273273) and Specialized Fund for Joint Building Program of Beijing Municipal Education Commission.
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Lv, P., Zhao, Q. (2015). Tracking Deformable Target via Multi-cues Active Contours. In: Ho, YS., Sang, J., Ro, Y., Kim, J., Wu, F. (eds) Advances in Multimedia Information Processing -- PCM 2015. PCM 2015. Lecture Notes in Computer Science(), vol 9314. Springer, Cham. https://doi.org/10.1007/978-3-319-24075-6_56
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DOI: https://doi.org/10.1007/978-3-319-24075-6_56
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