Extracting key frames from consumer videos using bi-layer group sparsity

Zheshen Wang, Mrityunjay Kumar, Jiebo Luo, Baoxin Li

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Scopus citations

Abstract

Compared to well-edited videos with predefined structures (e.g., news or sports videos), extracting key frames from unconstrained consumer videos remains a much more challenging problem due to their extremely diverse contents (no pre-imposed structure) and uncontrolled video quality (e.g., due to poor lighting or camera shake). In order to exploit spatio-temporal correlation present in the video for key frame extraction, we propose a bilayer group sparse representation in which the input video frames are first segmented into homogeneous patches and group sparsity is imposed at two levels simultaneously: (i) patch-to-frame, and (ii) frame-to-sequence. The grouped sparse coefficients are further combined with frame quality scores to generate key frames. Extensive experiments are performed on videos from actual end users. Results obtained by the proposed approach compare favorably with existing methods to confirm its effectiveness.

Original languageEnglish (US)
Title of host publicationMM'11 - Proceedings of the 2011 ACM Multimedia Conference and Co-Located Workshops
Pages1505-1508
Number of pages4
DOIs
StatePublished - Dec 29 2011
Event19th ACM International Conference on Multimedia ACM Multimedia 2011, MM'11 - Scottsdale, AZ, United States
Duration: Nov 28 2011Dec 1 2011

Publication series

NameMM'11 - Proceedings of the 2011 ACM Multimedia Conference and Co-Located Workshops

Other

Other19th ACM International Conference on Multimedia ACM Multimedia 2011, MM'11
CountryUnited States
CityScottsdale, AZ
Period11/28/1112/1/11

Keywords

  • Consumer video
  • Group sparsity
  • Key frame extraction

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design
  • Human-Computer Interaction

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  • Cite this

    Wang, Z., Kumar, M., Luo, J., & Li, B. (2011). Extracting key frames from consumer videos using bi-layer group sparsity. In MM'11 - Proceedings of the 2011 ACM Multimedia Conference and Co-Located Workshops (pp. 1505-1508). (MM'11 - Proceedings of the 2011 ACM Multimedia Conference and Co-Located Workshops). https://doi.org/10.1145/2072298.2072051