Robust 2D moving object segmentation and tracking in video sequences

Authors:
Vasile Gui;Florin Alexa;Catalin Caleanu;Daniela Fuiorea
Affiliations:
Department of Electronics and Telecommunications, "Politehnica" University Timisoara, Timisoara, Romania;Department of Electronics and Telecommunications, "Politehnica" University Timisoara, Timisoara, Romania;Department of Electronics and Telecommunications, "Politehnica" University Timisoara, Timisoara, Romania;Department of Electronics and Telecommunications, "Politehnica" University Timisoara, Timisoara, Romania
Venue:
ICOSSE'06 Proceedings of the 5th WSEAS international conference on System science and simulation in engineering
Year:
2006

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Abstract

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.