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An Effective News Anchorperson Shot Detection Method Based on Adaptive Audio/Visual Model Generation

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Image and Video Retrieval (CIVR 2005)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 3568))

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Abstract

A multi-modal method to improve the performance of the anchorperson shot detection for news story segmentation is proposed in this paper. The anchorperson voice information is used for the verification of anchorperson shot candidates extracted by visual information. The algorithm starts with the anchorperson voice shot candidate extraction using time and silence condition. The anchorperson templates are generated from the anchorperson face and cloth information from the anchorperson voice shots extracted. The anchorperson voice models are then created after segregating anchorperson voice shots containing 2 or more voices. The anchorperson voice model verifies the anchorperson shot candidates obtained from visual information. 720 minutes of news programs are tested and experimental results are demonstrated.

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© 2005 Springer-Verlag Berlin Heidelberg

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Kim, SK., Hwang, D.S., Kim, JY., Seo, YS. (2005). An Effective News Anchorperson Shot Detection Method Based on Adaptive Audio/Visual Model Generation. In: Leow, WK., Lew, M.S., Chua, TS., Ma, WY., Chaisorn, L., Bakker, E.M. (eds) Image and Video Retrieval. CIVR 2005. Lecture Notes in Computer Science, vol 3568. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11526346_31

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  • DOI: https://doi.org/10.1007/11526346_31

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-27858-0

  • Online ISBN: 978-3-540-31678-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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