AUDIO CLASSIFICATION AND SEGMENTATION FOR SPORTS VIDEO STRUCTURE EXTRACTION USING SUPPORT VECTOR MACHINE

摘要：

Video structure extraction is essential to automatic and content-based organization, retrieval and browsing of video.In this paper, we present a novel scheme for indexing and segmentation of video by analyzing the audio track using support vector machine. This analysis is then applied to structuring the sports video. Based on the attributes of sports video, we define three audio classes in sports video, namely Play-audio, Advertisement-audio and Studio-audio. Support vector machine (SVM) is a valid statistic learning method. The work on audio classification using SVM is presented. Meanwhile, considering that it is highly impossible to change the audio types too suddenly, we apply smoothing rules in final segmentation of an audio sequence. Experimental results indicate that our framework can produce satisfactory results.

关键词： Video structure extraction audio classification and segmentation support vector machine

作者: LIANG BAI SONG-YANG LAO HU-XIONG LIAO JIAN-YUN CHEN

作者单位: Multimedia Research and Development Center, National Univ.of Defense Technology, Changsha 410073 Hun Beijing Graphic and Image Research School, Beijing 100053, China

会议类型: 国际会议

会议名称: 2006 International Conference on Machine Learning and Cybernetics(IEEE第五届机器学习与控制论坛)

会议地点: 大连

会议语种:英文

页码: 3303-3307

在线出版日期: 2006-08-13（万方平台首次上网日期，不代表论文的发表时间）