Multimedia Tools and Applications

, Volume 76, Issue 5, pp 6521–6549 | Cite as

SurvSurf: human retrieval on large surveillance video data

  • Sihao Ding
  • Gang Li
  • Ying Li
  • Xinfeng Li
  • Qiang Zhai
  • Adam C. Champion
  • Junda Zhu
  • Dong Xuan
  • Yuan F. Zheng
Article

Abstract

The volume of surveillance videos is increasing rapidly, where humans are the major objects of interest. Rapid human retrieval in surveillance videos is therefore desirable and applicable to a broad spectrum of applications. Existing big data processing tools that mainly target textual data cannot be applied directly for timely processing of large video data due to three main challenges: videos are more data-intensive than textual data; visual operations have higher computational complexity than textual operations; and traditional segmentation may damage video data’s continuous semantics. In this paper, we design SurvSurf, a human retrieval system on large surveillance video data that exploits characteristics of these data and big data processing tools. We propose using motion information contained in videos for video data segmentation. The basic data unit after segmentation is called M-clip. M-clips help remove redundant video contents and reduce data volumes. We use the MapReduce framework to process M-clips in parallel for human detection and appearance/motion feature extraction. We further accelerate vision algorithms by processing only sub-areas with significant motion vectors rather than entire frames. In addition, we design a distributed data store called V-BigTable to structuralize M-clips’ semantic information. V-BigTable enables efficient retrieval on a huge amount of M-clips. We implement the system on Hadoop and HBase. Experimental results show that our system outperforms basic solutions by one order of magnitude in computational time with satisfactory human retrieval accuracy.

Keywords

Video analysis Surveillance MapReduce 

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Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  • Sihao Ding
    • 1
  • Gang Li
    • 2
  • Ying Li
    • 1
  • Xinfeng Li
    • 2
  • Qiang Zhai
    • 2
  • Adam C. Champion
    • 2
  • Junda Zhu
    • 3
  • Dong Xuan
    • 2
  • Yuan F. Zheng
    • 1
  1. 1.Department of Electrical and Computer EngineeringThe Ohio State UniversityColumbusUSA
  2. 2.Department of Computer Science and EngineeringThe Ohio State UniversityColumbusUSA
  3. 3.Department of Electrical and Computer EngineeringUniversity of MacauMacauChina

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