Keyframe Extraction from Human Motion Capture Data Based on a Multiple Population Genetic Algorithm

摘要

To reduce reconstruction errors during keyframe extraction and to control the optimal compression ratio, this study proposes a method for keyframe extraction from human motion capture data based on a multiple population genetic algorithm. The fitness function is defined to meet the goals of minimal reconstruction errors and the optimal compression rate, where multiple initial populations are subjected to co-evolution. The multiple population genetic algorithm considers global and local search. Experimental results showed that the algorithm can effectively extract the keyframe from motion capture data and it satisfied the desired reconstruction error.