In this article, we present a fast and high quality stereo matching algorithm on FPGA using cost aggregation (CA) and fast locally consistent (FLC) dense stereo. In many software programs, global matching algorithms are used in order to obtain accurate disparity maps. Although their error rates are considerably low, their processing speeds are far from that required for real-time processing because of their complex processing sequences. In order to realize real-time processing, many hardware systems have been proposed to date. They have achieved considerably high processing speeds; however, their error rates are not as good as those of software programs, because simple local matching algorithms have been widely used in those systems. In our system, sophisticated local matching algorithms (CA and FLC) that are suitable for FPGA implementation are used to achieve low error rate while maintaining the high processing speed. We evaluate the performance of our circuit on Xilinx Vertex-6 FPGAs. Its error rate is comparable to that of top-level software algorithms, and its processing speed is nearly 2 clock cycles per pixel, which reaches 507.9 fps for 640 × 480 pixel images. ACM Reference Format:Jin, M. and Maruyama, T. 2014. Fast and accurate stereo vision system on FPGA.

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Many hardware systems for stereo vision have been proposed. Their processing speed is very fast, but the algorithms used in them are limited in order to achieve the high processing speed by simplifying the sequences of the memory accesses and operations. The error rates by them can not compete with those by software programs. In this paper, we describe an FPGA implementation of a tree-structured dynamic programming algorithm. The computational complexity of this algorithm is higher than those by previous hardware systems, but the processing speed of our system is still fast enough for real-time applications, and its error rate is competitive with software algorithms.

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