An adaptive model generation technique for model-based video coding

نویسندگان

  • Manson Siu
  • Yuk-Hee Chan
چکیده

In conventional model-based coding schemes, predefined static models are generaliy used. Thesa models cannot adapt to new situations and hence they have to be very specific and cannot be generated from a single generic model even though they are very similar. In this paper, we present a model generation technique that can gradually build a model and dynamically modify it according to new video frames scanned. The proposed technique is robust to the object's orientation in the view and can be efficiently implemented with parallel processing lechnique. As a result, the proposed technique is more attractive to the practical use of model-based coding techniques in real applications.

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تاریخ انتشار 1999