Real-time stereo vision: making more out of dynamic programming, Computer Analysis of Images and Patterns

Abstract. Dynamic Programming (DP) is a popular and efficient method for cal-culating disparity maps from stereo images. It allows for meeting real-time con-straints 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. How-ever it is more flexible and shows increased performance. In particular, we intro-duce 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 % com-pared to the DP reference implementation while the overall complexity increased only slightly.