TY - EJOU AU - Bian, Jilong AU - Li, Jinfeng TI - Stereo Matching Method Based on Space-Aware Network Model T2 - Computer Modeling in Engineering \& Sciences PY - 2021 VL - 127 IS - 1 SN - 1526-1506 AB - The stereo matching method based on a space-aware network is proposed, which divides the network into three sections: Basic layer, scale layer, and decision layer. This division is beneficial to integrate residue network and dense network into the space-aware network model. The vertical splitting method for computing matching cost by using the space-aware network is proposed for solving the limitation of GPU RAM. Moreover, a hybrid loss is brought forward to boost the performance of the proposed deep network. In the proposed stereo matching method, the space-aware network is used to calculate the matching cost and then cross-based cost aggregation and semi-global matching are employed to compute a disparity map. Finally, a disparity-post processing method is utilized such as subpixel interpolation, median filter, and bilateral filter. The experimental results show this method has a good performance on running time and accuracy, with a percentage of erroneous pixels of 1.23% on KITTI 2012 and 1.94% on KITTI 2015. KW - Deep learning; stereo matching; space-aware network; hybrid loss DO - 10.32604/cmes.2021.014635