A fast stereo matching algorithm suitable for embedded real-time systems
Computer Vision and Image Understanding
Real-time high-definition stereo matching on FPGA
Proceedings of the 19th ACM/SIGDA international symposium on Field programmable gate arrays
Real-time stereo on GPGPU using progressive multi-resolution adaptive windows
Image and Vision Computing
Stereo matching using weighted dynamic programming on a single-direction four-connected tree
Computer Vision and Image Understanding
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Dynamic Programming (DP) is a popular and efficient method for calculating disparity maps from stereo images. It allows for meeting real-time constraints even on low-cost hardware. Therefore, it is frequently used in real-world applications, although more accurate algorithms exist. We present a refined DP stereo processing algorithm which is based on a standard implementation. However it is more flexible and shows increased performance. In particular, we introduce the idea of multi-path backtracking to exploit the information gained from DP more effectively. We show how to automatically tune all parameters of our approach offline by an evolutionary algorithm. The performance was assessed on benchmark data. The number of incorrect disparities was reduced by 40 % compared to the DP reference implementation while the overall complexity increased only slightly.