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

  • Raju Dhanakshirur RohanEmail author
  • Zeba ara Patel
  • Smita C. Yadavannavar
  • C. Sujata
  • Uma Mudengudi
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 1019)


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.


Video summarization Graph cut Geometric features Dempster Shafer Combination Rule (DSCR) 


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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Raju Dhanakshirur Rohan
    • 1
    Email author
  • Zeba ara Patel
    • 1
  • Smita C. Yadavannavar
    • 1
  • C. Sujata
    • 1
  • Uma Mudengudi
    • 1
  1. 1.KLE Technological UniversityHubliIndia

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