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Belief propagation (BP) is an effective algorithm for solving energy minimization problems in computer vision. However, it requires enormous memory, bandwidth, and computation because messages are iteratively passed between nodes in the Markov random field (MRF). In this paper, we propose two methods to address this problem. The first method is a message passing scheme called tile-based belief propagation...
Belief propagation has become a popular technique for solving computer vision problems, such as stereo estimation and image denoising. However, it requires large memory and bandwidth, and hence naive hardware implementation is prohibitive. In this paper, we first analyze the memory and bandwidth requirements of the technique from the hardware perspective. Then, we propose a tile-based belief propagation...
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