@Article{cmes.2021.014635,
AUTHOR = {Jilong Bian, Jinfeng Li},
TITLE = {Stereo Matching Method Based on Space-Aware Network Model},
JOURNAL = {Computer Modeling in Engineering \& Sciences},
VOLUME = {127},
YEAR = {2021},
NUMBER = {1},
PAGES = {175--189},
URL = {http://www.techscience.com/CMES/v127n1/41955},
ISSN = {1526-1506},
ABSTRACT = {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.},
DOI = {10.32604/cmes.2021.014635}
}