Video sequence segmentation using genetic algorithms

Abstract

This paper proposes a new video sequence segmentation method based on the genetic algorithm (GA) that can improve computational efficiency. The computation is distributed into chromosomes that evolve using distributed genetic algorithms (DGAs). Each chromosome consists of a label and feature vector. The label is used as the region number for the pixel where the chromosome is located. Based on the temporal correlation between two consecutive frames in a video sequence, the segmentation of a frame is successively obtained using the segmentation result of the previous frame. In addition to eliminating redundant computation, only unstable chromosomes corresponding to moving object parts are evolved. Experimental results confirm the effectiveness of the proposed method.