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Architectures for Computer Vision: From Algorithm to Chip with Verilog by Hong Jeong

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14 Belief Propagation for Stereo Matching

In Chapter 1, we surveyed vision systems in terms of algorithms and implementations. Especially good surveys have been done on real-time systems with BP (Tippetts et al. 2011) and with others (Tippetts et al. 2013). Unfortunately, most of the published works do not provide us with any source codes for actual designs, without which we cannot reconstruct an actual system. The purpose of this chapter is to develop an actual BP machine in Verilog HDL code (IEEE 2005) in order to equip readers to develop more advanced systems.

Belief propagation is a general method for solving optimization problems (Yedidia et al. 2003). In this chapter, we will design a BP circuit especially for stereo matching (Jian et al. 2003). However, although it is targeted at stereo matching, the design is general because by changing the data term together with other parameters, it can be used in many other vision problems, such as segmentation and motion estimation (Szeliski et al. 2008).

BP searches for the global optimal solution by iterative message passing. Since these messages are computed simultaneously for overall pixels per single iteration step, massive amount of computation and memory are required. Nevertheless, there are several high-speed implementations of stereo BP algorithm (Felzenszwalb and Huttenlocher 2004; Grauer-Gray and Kambhamettu 2009; Yang et al. 2006, 2009).

Due to high complexity of the algorithm, various works have tried to reduce computations ...

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