DWT-based Shot Boundary Detection Using Support Vector Machine

摘要：

Video shot detection is an important contemporary problem since it is the first step toward automatic indexing, content based video retrieval and many other different applications. A novel shot boundary detection using wavelet and Support Vector Machine is proposed in this paper. Shot boundary detection algorithms work by extracting the color and the edge in different direction from wavelet transition coefficients. A multi-class support vector machine (SVM) classifier is used to classify the video shot into three categories: cut transition(CT), gradual transition(GT) and normal sequences (NF). To enhance the robustness of the algorithm, we form the feature vector from all frames within a temporal window. Numerical experiments using a variety of videos demonstrate that our method is capable of accurately detecting and discriminating shot transitions in videos with different characteristics.

关键词： Shot Boundary Detection Support Vector Machine DWT

作者: Jun Li Youdong Ding Yunyu Shi Qingyue Zeng

作者单位: School of Computer Engineering and Science Shanghai University Shanghai,China

会议类型: 国际会议

会议名称: The Fifth International Conference on Information Assurance and Security(第五届信息保障与安全国际会议)

会议地点: 西安

会议语种:英文

页码: 435-438

在线出版日期: 2009-08-18（万方平台首次上网日期，不代表论文的发表时间）