Robust 2D Moving Object Segmentation and Tracking in Video Sequences

نویسندگان

  • VASILE GUI
  • FLORIN ALEXA
  • CATALIN CALEANU
  • DANIELA FUIOREA
چکیده

− Unsupervised motion segmentation and tracking in video sequences is a complex task, requiring robust estimation and flexible modeling. The paper presents an unsupervised method of moving object segmentation and tracking in video sequences captured by static cameras. Central to our work is the nonparametric density estimation and the mean shift algorithm for finding local maxima of the probability density. Foreground segmentation obtained from background estimation is combined with simultaneous region tracking and segmentation followed by connectivity-based moving object segmentation, in order to obtain an efficient processing algorithm. Preliminary tests asses the viability of the proposed approach.

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تاریخ انتشار 2006