IEEE Trans Image Process - Fast video shot boundary detection based on SVD and pattern matching.

Tópicos

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Resumo

Video shot boundary detection (SBD) is the first and essential step for content-based video management and structural analysis. Great efforts have been paid to develop SBD algorithms for years. However, the high computational cost in the SBD becomes a block for further applications such as video indexing, browsing, retrieval, and representation. Motivated by the requirement of the real-time interactive applications, a unified fast SBD scheme is proposed in this paper. We adopted a candidate segment selection and singular value decomposition (SVD) to speed up the SBD. Initially, the positions of the shot boundaries and lengths of gradual transitions are predicted using adaptive thresholds and most non-boundary frames are discarded at the same time. Only the candidate segments that may contain the shot boundaries are preserved for further detection. Then, for all frames in each candidate segment, their color histograms in the hue-saturation-value) space are extracted, forming a frame-feature matrix. The SVD is then performed on the frame-feature matrices of all candidate segments to reduce the feature dimension. The refined feature vector of each frame in the candidate segments is obtained as a new metric for boundary detection. Finally, cut and gradual transitions are identified using our pattern matching method based on a new similarity measurement. Experiments on TRECVID 2001 test data and other video materials show that the proposed scheme can achieve a high detection speed and excellent accuracy compared with recent SBD schemes.

Resumo Limpo

video shot boundari detect sbd first essenti step contentbas video manag structur analysi great effort paid develop sbd algorithm year howev high comput cost sbd becom block applic video index brows retriev represent motiv requir realtim interact applic unifi fast sbd scheme propos paper adopt candid segment select singular valu decomposit svd speed sbd initi posit shot boundari length gradual transit predict use adapt threshold nonboundari frame discard time candid segment may contain shot boundari preserv detect frame candid segment color histogram huesaturationvalu space extract form framefeatur matrix svd perform framefeatur matric candid segment reduc featur dimens refin featur vector frame candid segment obtain new metric boundari detect final cut gradual transit identifi use pattern match method base new similar measur experi trecvid test data video materi show propos scheme can achiev high detect speed excel accuraci compar recent sbd scheme

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