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Open Access

Object Tracking in Crowded Video Scenes Based on the Undecimated Wavelet Features and Texture Analysis

EURASIP Journal on Advances in Signal Processing20072008:243534

Received: 9 October 2006

Accepted: 8 October 2007

Published: 12 November 2007


We propose a new algorithm for object tracking in crowded video scenes by exploiting the properties of undecimated wavelet packet transform (UWPT) and interframe texture analysis. The algorithm is initialized by the user through specifying a region around the object of interest at the reference frame. Then, coefficients of the UWPT of the region are used to construct a feature vector (FV) for every pixel in that region. Optimal search for the best match is then performed by using the generated FVs inside an adaptive search window. Adaptation of the search window is achieved by interframe texture analysis to find the direction and speed of the object motion. This temporal texture analysis also assists in tracking of the object under partial or short-term full occlusion. Moreover, the tracking algorithm is robust to Gaussian and quantization noise processes. Experimental results show that the proposed algorithm has good performance for object tracking in crowded scenes on stairs, in airports, or at train stations in the presence of object translation, rotation, small scaling, and occlusion.


Texture AnalysisTracking AlgorithmWavelet PacketObject TrackingQuantization Noise

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Authors’ Affiliations

Digital Media Lab, AICTC Research Center, Department of Computer Engineering, Sharif University of Technology, Tehran, Iran
Department of Electronic Systems Engineering, University of Essex, Colchester, UK


© M. Khansari et al. 2008

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.