The USC Andrew and Erna Viterbi School of Engineering USC Signal and Image Processing Institute USC Ming Hsieh Department of Electrical Engineering University of Southern California

Technical Report USC-SIPI-279

“Boundary-Control Vector (BCV) Motion Field Representation and Estimation By Using A Markov Random Field Model”

by Jin Li, Xinggang Lin and C.-C. Jay Kuo

January 1995

A new motion field representation based on the boundary-control vector (BCV) scheme for video coding is examined in this work. With this scheme, the motion field is characterized by a set of control vectors, which are motion vectors associated with the center points of blocks, and a set of boundary functions, which specify the continuity of the motion field across adjacent blocks. For BCV-based motion field estimation, an optimization framework based on the Markov random field model and a maximum a posterior (MAP) criterion is used. The new scheme effectively represents complex motions such as translation, rotation, zooming and deformation and does not require complex scene analysis. Compared with MPEG of similar decoded SNR (signal-to-noise ratio) quality, 15-35% bit rate saving can be achieved in the proposed scheme with a more pleasant visual quality.

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