A Novel Shot Boundary Detection Method Based on Genetic Algorithm-Support Vector Machine

摘要：

Shot boundary detection (SBD) plays an important role in content-based video retrieval. In this paper, a novel algorithm for SBD based on support vector machine (SVM) and genetic algorithm (GA) is proposed. First of all, features of pixel domain and compressed domain are synthetically extracted, and then organized into a multi-dimension vector by using the method of sliding window. Following that, the genetic algorithm is utilized to implement the simulation and iterative optimization towards parameters of SVM kernel function, then the model trained by the approximately optimal parameters is applied to judge and classify the frames of video, thus SBD is completed. The proposed algorithm solves the difficulty in parameter selection of SVM, and experimental results on the TREC-2001 video data set indicate the effectiveness and robustness of our algorithm.

关键词： shot boundary detection support vector machine genetic algorithm content-based video retrieval

作者: Xuemei Sun Long Zhao Mingwei Zhang

作者单位: College of Computer, Tianjin Polytechnic University, Tianjin, China

会议类型: 国际会议

会议名称: 2011 Third International Conference on Intelligent Human-Machine Systems and Cybernetics 第三届智能人机系统与控制论国际会议 IHMSC 2011

会议地点: 杭州

会议语种:英文

页码: 144-147

在线出版日期: 2011-08-26（万方平台首次上网日期，不代表论文的发表时间）