Pruned multi-level successive elimination algorithm for TV commercial recognition

Authors:
Houde Yang;Nan Liu;Yao Zhao;Zhenfeng Zhu
Affiliations:
Beijing Jiaotong University, Beijing, China;Beijing Jiaotong University, Beijing, China;Beijing Jiaotong University, Beijing, China;Beijing Jiaotong University, Beijing, China
Venue:
Proceedings of the Third International Conference on Internet Multimedia Computing and Service
Year:
2011

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Abstract

In this paper, an efficient duplicate matching algorithm, called pruned multi-level successive elimination (PMSE), is proposed for TV commercial recognition. To enhance the efficiency of filtering out the irrelevant candidates from a sizable database, a felicitous pruning strategy is adapted to the multi-level successive elimination by exploiting the similarity relations of all candidates that can be constructed off-line. By progressively partitioning the signatures into finer granularity representation, more candidates can be eliminated with low computational complexity through pruning process at coarse granularity level. Moreover, a well-designed commercial content signature based on visual spatial correlation and LBP-like coding method, i.e. multi-scale local signature representation, is presented to robustly resist the visual perception distortion. The promising experimental results show the efficiency and effectiveness of the proposed strategy on large video data set.