A unified scheme of shot boundary detection and anchor shot detection in news video story parsing

  • Authors:

  • Hansung Lee;Jaehak Yu;Younghee Im;Joon-Min Gil;Daihee Park

  • Affiliations:

  • Electronics and Telecommunications Research Institute, Daejeon, Republic of Korea;Department of Computer and Information Science, Korea University, Chochiwon, South Korea 339-700;Department of Computer and Information Science, Korea University, Chochiwon, South Korea 339-700;Department of Computer Science Education, Catholic University of Daegu, Gyeongsan-si, South Korea 712-702;Department of Computer and Information Science, Korea University, Chochiwon, South Korea 339-700

  • Venue:
  • Multimedia Tools and Applications
  • Year:
  • 2011

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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.