Analysis of belief propagation for hardware realization
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 algorithm that works with existing data reuse schemes and achieves bandwidth reduction by a factor of 10 to 400. We apply the proposed algorithm to stereo estimation and show that its performance is comparable to the original algorithm.