An Efficient Automatic Video Shot Size Annotation Scheme

Abstract. This paper presents an efficient learning scheme for automatic annotation of video shot size. Instead of existing methods that applied in sports videos using domain knowledge, we are aiming at a general approach to deal with more video genres, by using a more general low- and mid- level feature set. Support Vector Machine (SVM) is adopted in the classification task, and an efficient co-training scheme is used to explore the information embedded in unlabeled data based on two complementary feature sets. Moreover, the subjectivity-consistent costs for different mis-classifications are introduced to make the final decisions by a cost minimization criterion. Experimental results indicate the effectiveness and efficiency of the proposed scheme for shot size annotation.

• Type: Conference
• Year: 2007
• Where: MMM
• Authors: Meng Wang, Xian-Sheng Hua, Yan Song, Wei Lai, Li-Rong Dai, Ren-Hua Wang
• Keywords: Efficient Learning Scheme, Feature Sets, MMM 2007, Multimedia, Shot Size