Optimized Belief Propagation Algorithm onto Embedded Multi and Many-Core Systems for Stereo Matching

Abstract

Stereo matching techniques aim at reconstructing disparity maps from a pair of images. The use of stereo matching techniques in embedded systems is very challenging due to the complexity of the state-of-the-art algorithms. Local stereo matching algorithms are efficiently implemented on GPU and DSP. This paper presents the optimization of the One Dimension Belief Propagation (BP-1D) algorithm. BP-1D is faster than previous algorithms on monocore DSP and its implementation onto multicore DSPs is straightforward. BP-1D implemented on multicore embedded platforms out-performs previous stereo matching implementations reaching real-time performances for resolutions up to 1080p with a 10 Watts power consumption.