Genetic algorithm-based video segmentation with adaptive population size

Abstract

This paper presented a novel object-based video segmentation using genetic algorithms. The novelty of the approach is that the population size is not constant, but motion dependent. The population size depends on the degree of the motion. In our approach, the video segmentation is performed by two steps: initial segmentation and temporal tracking. Once the objects constituting the scenes, which are tracked through the whole video sequence. Then, the temporal tracking is carried out by chromosomes that evolve using distributed genetic algorithms (DGAs). Each chromosome has its own population size according to its motion amounts, and independently evolves using local evolutionary rules. The proposed method was tested with well-known video sequences, and the results confirmed its effectiveness in segmenting a video sequence. © Springer-Verlag Berlin Heidelberg 2003.