Title :
A Formal Study of Shot Boundary Detection
Author :
Yuan, Jinhui ; Wang, Huiyi ; Xiao, Lan ; Zheng, Wujie ; Li, Jianmin ; Lin, Fuzong ; Zhang, Bo
Author_Institution :
Dept. of Comput. Sci. & Eng., Tsinghua Univ., Beijing
Abstract :
This paper conducts a formal study of the shot boundary detection problem. First, a general formal framework of shot boundary detection techniques is proposed. Three critical techniques, i.e., the representation of visual content, the construction of continuity signal and the classification of continuity values, are identified and formulated in the perspective of pattern recognition. Meanwhile, the major challenges to the framework are identified. Second, a comprehensive review of the existing approaches is conducted. The representative approaches are categorized and compared according to their roles in the formal framework. Based on the comparison of the existing approaches, optimal criteria for each module of the framework are discussed, which will provide practical guide for developing novel methods. Third, with all the above issues considered, we present a unified shot boundary detection system based on graph partition model. Extensive experiments are carried out on the platform of TRECVID. The experiments not only verify the optimal criteria discussed above, but also show that the proposed approach is among the best in the evaluation of TRECVID 2005. Finally, we conclude the paper and present some further discussions on what shot boundary detection can learn from other related fields
Keywords :
graph theory; image classification; object detection; TRECVID; continuity signal construction; continuity values classification; graph partition model; pattern recognition; shot boundary detection; Computer science; Content based retrieval; Gunshot detection systems; Indexing; Multiresolution analysis; NIST; Pattern recognition; Signal processing; Support vector machines; Videos; Formal framework; graph partition model; multiresolution analysis; shot boundary detection; support vector machine (SVM);
Journal_Title :
Circuits and Systems for Video Technology, IEEE Transactions on
DOI :
10.1109/TCSVT.2006.888023