Abstract
In this paper, we propose an efficient one-pass algorithm for shot boundary detection and a cost-effective anchor shot detection method with search space reduction, which are unified scheme in news video story parsing. First, we present the desired requirements for shot boundary detection from the perspective of news video story parsing, and propose a new shot boundary detection method, based on singular value decomposition, and a newly developed algorithm, viz., Kernel-ART, which meets all of these requirements. Second, we propose a new anchor shot detection system, viz., MASD, which is able to detect anchor person cost-effectively by reducing the search space. It consists of skin color detector, face detector, and support vector data descriptions with non-negative matrix factorization sequentially. The experimental results with the qualitative analysis illustrate the efficiency of the proposed method.
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Acknowledgements
This research was supported by a Korea University Grant; This research was financially supported by the Ministry of Education, Science Technology (MEST) and Korea Industrial Technology Foundation (KOTEF) through the Human Resource Training Project for Regional Innovation.
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Lee, H., Yu, J., Im, Y. et al. A unified scheme of shot boundary detection and anchor shot detection in news video story parsing. Multimed Tools Appl 51, 1127–1145 (2011). https://doi.org/10.1007/s11042-010-0462-x
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DOI: https://doi.org/10.1007/s11042-010-0462-x