An Effective Video Shot Boundary Detection Method Based on Supervised Learning

摘要：

Video shot boundary detection plays an every important role in video processing. It is the first step toward video content analysis and content-based video retrieval. We develop a novel approach for video shot boundary detection based on supervised learning. Our method consists in first extracting video frame feature using a supervised kernel nonlocality preserving projections, then video frames are split into abrupt transitions, gradual transitions or normal frames using two cascaded Localized-SVM classifiers. Experimental results show the effectiveness of our method.

关键词： shot boundary detection supervised learning Non-locality preserving projections SVM

作者: Yongliang Xiao

作者单位: Department of Information Management Hunan College of Finance and Economics Changsha Hunan Province China

会议类型: 国际会议

会议名称: The 2nd IEEE International Conference on Advanced Computer Control(第二届先进计算机控制国际会议 ICACC 2010)

会议地点: 沈阳

会议语种:英文

页码: 371-374

在线出版日期: 2010-03-27（万方平台首次上网日期，不代表论文的发表时间）