@inproceedings{b57853f059f14558b44082812d1f1057,
title = "A novel camera calibration method for binocular vision based on improved RBF neural network",
abstract = "Considering the problems that camera imaging model is complex and operation is complicated, a binocular camera calibration method of RBF neural network based on k-means and gradient method is proposed in this paper. The data center selection method based on the law of clustering error function can obtain hidden nodes and data centers of RBF network accurately. Dynamic learning of data centers, spread constants and weight values based on gradient method can contribute to improving the precision. Experimental results show that the proposed method has high precision and can be well applied in machine vision.",
keywords = "Binocular vision, Camera calibration, Gradient method, K-means, RBF neural network",
author = "Weike Liu and Ju Huo and Xing Zhou and Ming Yang",
note = "Publisher Copyright: {\textcopyright} Springer Nature Singapore Pte Ltd. 2017.; 2nd Chinese Conference on Computer Vision, CCCV 2017 ; Conference date: 11-10-2017 Through 14-10-2017",
year = "2017",
doi = "10.1007/978-981-10-7299-4\_36",
language = "英语",
isbn = "9789811072987",
series = "Communications in Computer and Information Science",
publisher = "Springer Verlag",
pages = "439--448",
editor = "Xiang Bai and Qinghua Hu and Liang Wang and Qingshan Liu and Jinfeng Yang and Ming-Ming Cheng and Deyu Meng",
booktitle = "Computer Vision - 2nd CCF Chinese Conference, CCCV 2017, Proceedings",
address = "德国",
}