@inproceedings{b07b8bf552d24674ac1501f1c310fac4,
title = "Cross-scale cost aggregation for stereo matching",
abstract = "Human beings process stereoscopic correspondence across multiple scales. However, this bio-inspiration is ignored by state-of-the-art cost aggregation methods for dense stereo correspondence. In this paper, a generic cross-scale cost aggregation framework is proposed to allow multi-scale interaction in cost aggregation. We firstly reformulate cost aggregation from a unified optimization perspective and show that different cost aggregation methods essentially differ in the choices of similarity kernels. Then, an inter-scale regularizer is introduced into optimization and solving this new optimization problem leads to the proposed framework. Since the regularization term is independent of the similarity kernel, various cost aggregation methods can be integrated into the proposed general framework. We show that the cross-scale framework is important as it effectively and efficiently expands state-of-the-art cost aggregation methods and leads to significant improvements, when evaluated on Middlebury, KITTI and New Tsukuba datasets.",
keywords = "cost aggregation, multi-scale, stereo matching",
author = "Kang Zhang and Yuqiang Fang and Dongbo Min and Lifeng Sun and Shiqiang Yang and Shuicheng Yan and Qi Tian",
note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; null ; Conference date: 23-06-2014 Through 28-06-2014",
year = "2014",
month = sep,
day = "24",
doi = "10.1109/CVPR.2014.206",
language = "English",
series = "Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition",
publisher = "IEEE Computer Society",
pages = "1590--1597",
booktitle = "Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition",
}