Real-time GPU-based local stereo matching method

Stereo matching techniques aim at reconstruct the disparity maps with a pair of images. This paper propose a real-time stereo matching algorithm optimized for GPU platform. Our method first constructs the matching cost by combining measure of truncated absolute difference (TAD) cost and census cost;...

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Bibliographic Details
Published in2013 Conference on Design and Architectures for Signal and Image Processing pp. 209 - 214
Main Authors Jinglin Zhang, Nezan, Jean-Francois, Pelcat, Maxime, Cousin, Jean-Gabriel
Format Conference Proceeding
LanguageEnglish
Published European Electronic Chips & Systems design Initiative - ECSI 01.10.2013
Subjects
Accuracy
adaptive weight
Census
GPU
Graphics processing units
HMPP
Kernel
Parallel processing
Programming
Real-time systems
Stereo Matching
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Summary:Stereo matching techniques aim at reconstruct the disparity maps with a pair of images. This paper propose a real-time stereo matching algorithm optimized for GPU platform. Our method first constructs the matching cost by combining measure of truncated absolute difference (TAD) cost and census cost; then we aggregates matching costs using adaptive weight method and iterates with square step size in the horizontal and vertical pass. In addition, we implement our algorithm on GPU platform using a high level compiler HMPP (Hybrid Multicore Parallel Programming) which greatly reduces the development time and make use of the parallel computing of GPU device with CUDA (Compute Unified Device Architecture)/OpenCL (Open Computing Language). The GPU-based implementation of our method obtains 20 fps on a general laptop's GPU satisfying real-time requirement.