A Shot Boundary Detection Method Based on PSO-SVM

Long Zhao; Xue Mei Sun; Ming Wei Zhang

doi:10.4028/www.scientific.net/AMM.130-134.3821

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 130-134A Shot Boundary Detection Method Based on PSO-SVM

A Shot Boundary Detection Method Based on PSO-SVM

Abstract:

Shot boundary detection (SBD) is the first step which segments video data into elementary shots for content-based video retrieval. In this paper, a shot boundary detection algorithm based on support vector machine (SVM) and particle swarm optimization (PSO) is proposed. First of all, the extracted features of pixel domain and compressed domain are combined to form a multi-dimension feature vector by using the scheme of sliding window. Next, particle swarm optimization with global search capacity is adopted to seek the approximately optimal parameters of radial basis function of SVM. Finally the model trained by the parameters obtained is applied to judge and categorize the frames into cut transitions, gradual transitions and non-transitions. The experimental results on the TREC video set 2001 demonstrate our algorithm is efficient and robust, and it solves the difficulty in parameter selection of SVM well.

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Mechanical and Electronics Engineering III

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Periodical:

Applied Mechanics and Materials (Volumes 130-134)

Pages:

3821-3825

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.130-134.3821

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Online since:

October 2011

Authors:

Long Zhao, Xue Mei Sun, Ming Wei Zhang

Keywords:

Content-Based Video Retrieval, Particle Swarm Optimization Algorithm (PSO), Shot Boundary Detection, Support Vector Machine (SVM)

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