A Novel Approach for Robust Surveillance Video Content Abstraction

نویسندگان

  • Limin Wang
  • Yirui Wu
  • Zhiyuan Tian
  • Zailiang Sun
  • Tong Lu
چکیده

Efficient video content analysis is an unsolved problem, especially for real-life surveillance videos due to their low resolution and illustration variations. A novel framework to efficiently and robustly convert a surveillance video clip into one abstraction image containing the integrated contour of interested objects is proposed. It has the following novelties: 1) an improved w-SIFT algorithm for Y-axis frames offset calculation, 2) a trapezoid-based compensation algorithm for X-axis perspective distortion correction, and 3) an incremental video content integration approach. Experimental results show that our method is robust for real-life low resolution videos and efficient for real-time analysis.

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تاریخ انتشار 2010