Yuanyuan Wang^1,*, Rui Wang², Xiaofeng Ren³, Junan Lei²

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.2, pp. 1951-1972, 2023, DOI:10.32604/cmes.2023.026112 - 06 February 2023

Abstract The dense and accurate measurement of 3D texture is helpful in evaluating the pavement function. To form dense mandatory constraints and improve matching accuracy, the traditional binocular reconstruction technology was improved threefold. First, a single moving laser line was introduced to carry out global scanning constraints on the target, which would well overcome the difficulty of installing and recognizing excessive laser lines. Second, four kinds of improved algorithms, namely, disparity replacement, superposition synthesis, subregion segmentation, and subregion segmentation centroid enhancement, were established based on different constraint mechanism. Last, the improved binocular reconstruction test device was More >

Jilong Bian^1,*, Jinfeng Li²

CMES-Computer Modeling in Engineering & Sciences, Vol.127, No.1, pp. 175-189, 2021, DOI:10.32604/cmes.2021.014635 - 30 March 2021

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 More >