Multiple objects tracking finds its applications in many high level vision analysis like object behaviourinterpretation and gait recognition. In this paper, a feature based method to track the multiple movingobjects in surveillance video sequence is proposed. Object tracking is done by extracting the color and Humoments features from the motion segmented object blob and establishing the association of objects in thesuccessive frames of the video sequence based on Chi-Square dissimilarity measure and nearest neighborclassifier. The benchmark IEEE PETS and IEEE Change Detection datasets has been used to show therobustness of the proposed method. The proposed method is assessed quantitatively using the precision andrecall accuracy metrics. Further, comparative evaluation with related works has been carried out to exhibitthe efficacy of the proposed method.
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