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A Fast Active Contour Tracking Method Based on Gaussian Mixture Model

Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 246)

Abstract

This paper proposed a Gaussian mixture model based gradient level set method (GMM-GLS) for moving target contour tracking in video sequences to handle automatic initialization and background variation. In contrast with conventional level set models, adaptive GMM background subtraction is applied to get the rough location of moving target as foreground in current frame. And more accurate mask image according to the rough location of foreground with dilatation operation indicates the initialization contour of level set evolution. Then, the gradient level set model can evolve the curve quickly and ensure more accurate convergence to the target contour in tracking procedure. Based on this accurate mask, the GMM-GLS method can greatly reduce the uncertain iteration time in curve convergence and optimize the initialization of GLS eliminating the interferential background. Experimental results on many real-world video sequences validate that our approach greatly improves the performance of object contour tracking.

Keywords

Geometric active contours Level set Gaussian mixture model 

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.School of Communication and Information EngineeringShanghai UniversityShanghaiChina
  2. 2.Shanghai Key Laboratory of Digital Media Processing and TransmissionsShanghai Jiao Tong UniversityShanghaiChina

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