An object tracking scheme based on local density

  • Authors:
  • Zhuan Qing Huang;Zhuhan Jiang

  • Affiliations:
  • School of Computing and Mathematics, University of Western Sydney, NSW, Australia;School of Computing and Mathematics, University of Western Sydney, NSW, Australia

  • Venue:
  • MMM'07 Proceedings of the 13th international conference on Multimedia Modeling - Volume Part I
  • Year:
  • 2007

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Abstract

We propose a method for tracking an object from a video sequence of moving background through the use of the proximate distribution densities of the local regions. The discriminating features of the object are extracted from a small neighborhood of the local region containing the tracked object. The object's location probability is estimated in a Bayesian framework with the prior being the approximated probabilities in the previous frame. The proposed method is both practical and general since a great many of video scenes are included in this category. For the case of less-potent features, however, additional information from such as the motion is further integrated to help improving the estimation of location probabilities of the object. The non-statistical location of an object is then derived through thresholding and shape adjustment, as well as being verified by the prior density of the object. The method is effective and robust to occlusion, illumination change, shape change and partial appearance change of the object.