@inproceedings{20576bcb16764cecaef68b624e99e14e,
title = "Stereo matching with improved radiometric invariant matching cost and disparity refinement",
abstract = "Accurate and real-time stereo correspondence is a pressing need for many computer vision applications. In this paper, an improved radiometric invariant matching cost algorithm is proposed. It effectively combines modified census transform with relative gradients measures. Although it is very simple, comparison results on Middlebury stereo testbed demonstrate that it has much lower error rates than many existing algorithms and is very close to the ANCC algorithm which represents the current state of the art under extreme luminance condition but outperforms the ANCC algorithm greatly when there are small radiometric distortions. In addition, we also develop a disparity refinement method with computational complexity invariant to the disparity range. Experimental results on Middlebury datasets show those artifacts near object boundaries are reduced using the proposed disparity refinement method.",
keywords = "Census transform, Disparity refinement, Radiometric invariant, Stereo matching",
author = "Jinjin Shi and Fangfa Fu and Yao Wang and Weizhe Xu and Jinxiang Wang",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2016.; 12th International Conference on Intelligent Computing, ICIC 2016 ; Conference date: 02-08-2016 Through 05-08-2016",
year = "2016",
doi = "10.1007/978-3-319-42291-6\_7",
language = "英语",
isbn = "9783319422909",
series = "Lecture Notes in Computer Science",
publisher = "Springer Verlag",
pages = "61--73",
editor = "De-Shuang Huang and Vitoantonio Bevilacqua and Prashan Premaratne",
booktitle = "Intelligent Computing - 12th International Conference, ICIC 2016, Proceedings",
address = "德国",
}