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Image Segmentation and Geometric Feature Based Approach for Fast Video Summarization of Surveillance Videos

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Computer Vision Applications (WCVA 2018)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1019))

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Abstract

In this paper, we propose a geometric feature and frame segmentation based approach for video summarization. Video summarization aims to generate a summarized video with all the salient activities of the input video. We propose to retain the salient frames towards generation of video summary. We detect saliency in foreground and background of the image separately. We propose to model the image as MRF (Markov Random Field) and use MAP (Maximum a-posteriori) as final solution to segment the image into foreground and background. The salient frame is defined by the variation in feature descriptors using the geometric features. We propose to combine the probabilities of foreground and background segments being salient using DSCR (Dempster Shafer Combination Rule). We consider the summarized video as a combination of salient frames for a user defined time. We demonstrate the results using several videos in BL-7F dataset and compare the same with state of art techniques using retention ratio and condensation ratio as quality parameters.

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Authors and Affiliations

  1. KLE Technological University, Hubli, India

    Raju Dhanakshirur Rohan, Zeba ara Patel, Smita C. Yadavannavar, C. Sujata & Uma Mudengudi

Authors
  1. Raju Dhanakshirur Rohan
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  2. Zeba ara Patel
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  3. Smita C. Yadavannavar
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  4. C. Sujata
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  5. Uma Mudengudi
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Corresponding author

Correspondence to Raju Dhanakshirur Rohan .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, Indian Institute of Technology Delhi, New Delhi, India

    Chetan Arora

  2. Department of Electrical Engineering, Indian Institute of Technology Madras, Chennai, India

    Kaushik Mitra

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Rohan, R.D., ara Patel, Z., Yadavannavar, S.C., Sujata, C., Mudengudi, U. (2019). Image Segmentation and Geometric Feature Based Approach for Fast Video Summarization of Surveillance Videos. In: Arora, C., Mitra, K. (eds) Computer Vision Applications. WCVA 2018. Communications in Computer and Information Science, vol 1019. Springer, Singapore. https://doi.org/10.1007/978-981-15-1387-9_7

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  • DOI: https://doi.org/10.1007/978-981-15-1387-9_7

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-1386-2

  • Online ISBN: 978-981-15-1387-9

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