Motion segmentation based on a new genetic algorithm
Yuzhen Li , Mingying Fan, Ghoneim Mohamed, Jianming Lu, Hiroo Sekiya, and Takashi Yahagi
2007 RISP International Workshop on Nonlinear Circuits and Signal Processing (NCSP2007), pp.543-546, Mar., 2007. [pdf document]

<Abstract>

Inspired by the paper [11], we introduce a new motion segmentation method which combines the spatial segmentation and temperal segmentation together. First we construct the image model based on the Markov Random Fields (MRF) for each frame. Then the segmentation is represented by the minimization of a posterior energy function. We use the genetic algorithm(GA) to find the solutions. The background differecing and evolution probability are combined to find the unstable individuals. The advantage of this method is that it decrease the number of the evolution individuals and decrease the computation time consuming.