Moving objects segmentation based on piecewise constant Mumford-Shah model solving by additive operator splitting

作者：Wang Dengwei^*; Zhang Tianxu; Shi Wenjun; Wang Zhonghua; Yang Xiaoyu; Wei Longsheng

来源：Optical Engineering, 2010, 49(3): 037004.

DOI：10.1117/1.3363833

• moving objects
• segmentation
• piecewise constant Mumford-Shah model
• additive operator splitting (AOS)
• Gaussian mixture model (GMM)

We propose a moving objects segmentation method for color image sequences based on the piecewise constant Mumford-Shah model (also known as the C-V model) solving by the semi-implicit additive operator splitting (AOS) scheme, which is unconditionally stable, fast, and easy to implement. The method first uses the Gaussian mixture model for background modeling and then subtracts the background to obtain the moving regions that are the handling objects of our method. As a result of the introduction of the AOS scheme, we could use a rather large time step and still maintain the stability of the evolution process. Additionally, the method can easily be parallelized because the AOS scheme decomposes the equations into a sequence of one-dimensional (1-D) systems. The experimental results demonstrate that under real moving objects video tests, the AOS scheme accelerates the evolution of the curve and significantly reduces the number of iterations, and also demonstrates the validity of our method.

• 出版日期2010-3
• 单位华中科技大学; 中国人民解放军海军航空工程学院