Object based segmentation of video using variational level sets

Authors:
Cheng Bing;Wang Ying;Zheng Nanning;Bian Zhengzhong
Affiliations:
Artificial Intelligence and Robotics Institute, Xi'an Jiaotong University, Xi'an, China and Department of Biomedical Engeering, Xi'an Jiaotong University, Xi'an, China;Medical experiment center of hospital, Xi'an Jiaotong University, Xi'an, China;Artificial Intelligence and Robotics Institute, Xi'an Jiaotong University, Xi'an, China;Department of Biomedical Engeering, Xi'an Jiaotong University, Xi'an, China
Venue:
Machine Graphics & Vision International Journal
Year:
2005

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Abstract

The paper demonstrates a new approach to video segmentation which retains some of the attractive features of existing methods and overcomes some of their limitations. The video sequence is represented as a spatio-temporal volume, and is segmented by an extension of active contour model based on Mumford-Shah techniques. The energy function minimization is similar to 3D interface evolution with curvature-dependent speeds. The spatio-temporal volume need not to be smoothed before processing because our method is not sensitive to noise. Each object needs a closed interface, which is embedded as a level set of a higher-dimensional functions, and is propagated by solving a partial differential equation. The interface stops in the vicinity of object boundaries, which are not necessarily defined by the gradient and can be represented with complex topologies. Finally, an experiment is given to show the effectiveness and robustness of the method.