@inproceedings{ec17ea296c204f7d92ad4531b5859867,
title = "The SGM Algorithm based on Census Transform for Binocular Stereo Vision",
abstract = "Aiming to reduce the error matching rate of binocular image matching and improve the accuracy of disparity map, the matching cost calculation method of Semi-Global Matching (SGM) algorithm is improved, the Census transform and adaptive window is used to calculate the cost simultaneously, and the size and shape of the cost calculation window are determined by judging the gradient size of matching points, which improves the matching accuracy and reduces the computational complexity of the algorithm. Experimental results show that the proposed algorithm can effectively improve the accuracy of binocular ranging.",
keywords = "Census transform, SGM algrithm, binocular image matching, disparity map",
author = "Liye Zhang and Fudong Cai and Jinjun Wang and Changfeng Lv and Wei Liu and Guoxin Guo and Huanyun Liu",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 2022 International Conference on Machine Learning and Knowledge Engineering, MLKE 2022 ; Conference date: 25-02-2022 Through 27-02-2022",
year = "2022",
doi = "10.1109/MLKE55170.2022.00015",
language = "英语",
series = "Proceedings - 2022 International Conference on Machine Learning and Knowledge Engineering, MLKE 2022",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "50--54",
booktitle = "Proceedings - 2022 International Conference on Machine Learning and Knowledge Engineering, MLKE 2022",
}