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Automatic TV Logo Detection, Tracking and Removal in Broadcast Video

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Advances in Multimedia Modeling (MMM 2007)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 4352))

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Abstract

TV logo detection, tracking and removal play an important role in the applications of claiming video content ownership, logo-based broadcasting surveillance, commercial skipping, and program rebroadcasting with new logos. In this paper, we present a novel and robust framework using tensor method for these three tasks. First, we use tensor based generalized gradient and the OTSU binarization algorithm to logo detection, and propose a two level framework from coarse to fine to tracking the TV logos. Finally, we extend the regularization PDEs by incorporation of temporal information to inpaint the logo region. Due to the introduction of the structure tensor, the generalized gradient based method can detect the logo region by tracking the change rate of pixels in spatio-temporal domain, and the region of logo removal is well filled in a structure-preserving way. Since temporal correlation of multiple consecutive frames is considered, the proposed method can deal with opaque, semi-transparent, and animated logos. The experiments and comparison with previous methods are conducted on the part of TRECVID 2005 news corpus and several Chinese TV channels with challenging TV logos, and the experimental results are promising.

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© 2006 Springer-Verlag Berlin Heidelberg

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Wang, J., Liu, Q., Duan, L., Lu, H., Xu, C. (2006). Automatic TV Logo Detection, Tracking and Removal in Broadcast Video. In: Cham, TJ., Cai, J., Dorai, C., Rajan, D., Chua, TS., Chia, LT. (eds) Advances in Multimedia Modeling. MMM 2007. Lecture Notes in Computer Science, vol 4352. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69429-8_7

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  • DOI: https://doi.org/10.1007/978-3-540-69429-8_7

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-69428-1

  • Online ISBN: 978-3-540-69429-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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