Video Segmentation and Summarization Based on Genetic Algorithm

摘要：

This paper presents a Binary Genetic Algorithms (BGA) based video summarization system. The similarity functions are first defined to evaluate segmentation, which are extremely expensive to be optimized with traditional methods. Then the system employs binary crossover and mutation operators to get the meaningful summary in a video search space. In order to test performance of the BGA method, we first compare the BGA method with Decimal Genetic Algorithms (DGA) method. The obtained results show that it is more quickly to find the best results for BGA than DGA. Second, the BGA method and the uniform approach have been compared. Experimental results show that the BGA method can capture more information than the uniform method and reduce redundancy.

关键词： video summarization keyframe genetic algorithms fitness function

作者: Yang Xue Wei Zhicheng

作者单位: College of Physical Science and Information Engineering Hebei Normal University Shijiazhuang, China

会议类型: 国际会议

会议名称: 2011 4th International Congress on Image and Signal Processing(第四届图像与信号处理国际学术会议 CISP 2011)

会议地点: 上海

会议语种:英文

页码: 470-474

在线出版日期: 2011-10-15（万方平台首次上网日期，不代表论文的发表时间）