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Movie Video Summarization- Generating Personalized Summaries Using Spatiotemporal Salient Region Detection

Author

Listed:
  • Rajkumar Kannan

    (Bishop Heber College, Tiruchirappalli, India)

  • Sridhar Swaminathan

    (Bennett University, Greater Noida, India)

  • Gheorghita Ghinea

    (School of Information Systems, Computing and Mathematics, Brunel University, Uxbridge, UK & Norwegian School of Information Technology, Oslo, Norway)

  • Frederic Andres

    (National Institute of Informatics, Chiyoda City, Japan)

  • Kalaiarasi Sonai Muthu Anbananthen

    (Multimedia University Malacca, Bukit Beruang, Malaysia)

Abstract

Video summarization condenses a video by extracting its informative and interesting segments. In this article, a novel video summarization approach is proposed based on spatiotemporal salient region detection. The proposed approach first segments a video into a set of shots which are ranked with spatiotemporal saliency scores. The score for a shot is computed by aggregating the frame level spatiotemporal saliency scores. This approach detects spatial and temporal salient regions separately using different saliency theories related to objects present in a visual scenario. The spatial saliency of a video frame is computed using color contrast and color distribution estimations and center prior integration. The temporal saliency of a video frame is estimated as an integration of local and global temporal saliencies computed using patch level optical flow abstractions. Finally, top ranked shots with the highest saliency scores are selected for generating the video summary. The objective and subjective experimental results demonstrate the efficacy of the proposed approach.

Suggested Citation

  • Rajkumar Kannan & Sridhar Swaminathan & Gheorghita Ghinea & Frederic Andres & Kalaiarasi Sonai Muthu Anbananthen, 2019. "Movie Video Summarization- Generating Personalized Summaries Using Spatiotemporal Salient Region Detection," International Journal of Multimedia Data Engineering and Management (IJMDEM), IGI Global, vol. 10(3), pages 1-26, July.
    • Handle: RePEc:igg:jmdem0:v:10:y:2019:i:3:p:1-26
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