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A novel feature fusion based framework for efficient shot indexing to massive web videos

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Abstract

This study addresses an automatic approach to analyze the structure of large scale web videos based on visual and acoustic information. In our approach, video streams are macro-segmented via mining the duplicate sequences. Acoustic and visual information are both adopted for mining so as to avoid missing true-positive. Web videos contain severe visual and acoustic distortions, differing to TV data, where duplicate clips are quite similar. In this case, we present novel visual-acoustic feature schemes to handle the distortions. And shot based indexing algorithm and several temporary constrains are presented to mine the duplicate sequences, where the weak geometric verification is combined with direct hashing to achieve high efficiency and superior performance of image-based duplicate sequences detection, and dynamic programming is introduced to recall missing true-positives in audio-based section. Experiments conducted on the dataset composed of 500 h content-unknown videos show that F-Measure of duplicate sequences mining for web videos can achieve the rate of 95 % and, in terms of efficiency and detection performance, the proposed algorithm outperforms the state-of-art approaches.

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Notes

  1. http://ffmpeg.org.

  2. http://www-nlpir.nist.gov/projects/tv2011/#ccd.

  3. http://sports.orange.fr/.

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Acknowledgments

This work is sponsored by collaborative Research Project (SEV01100474) between Beijing University of Posts and Telecommunications and France Telecom – Orange Lab Beijing, the National High Technology Research and Development Program of China (863 Program, No. 2012AA012505), and the National Natural Science Foundation of China (61372169).

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Authors and Affiliations

  1. Beijng University of Posts and Telecommunications, Beijing, 100876, People’s Republic of China

    Yuan Dong & Shusheng Cen

  2. France Telecom – Orange Lab Beijing, Beijing, 100190, People’s Republic of China

    Yuan Dong, Lezi Wang & Wei Liu

  3. Huawei Central Research Institute, Beijing, 100086, People’s Republic of China

    Shiguo Lian

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  1. Yuan Dong
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  2. Lezi Wang
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  3. Shiguo Lian
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  4. Shusheng Cen
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  5. Wei Liu
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Correspondence to Yuan Dong.

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Dong, Y., Wang, L., Lian, S. et al. A novel feature fusion based framework for efficient shot indexing to massive web videos. Telecommun Syst 59, 401–413 (2015). https://doi.org/10.1007/s11235-014-9945-9

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