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Feature Ensemble Network with Occlusion Disambiguation for Accurate Patch-Based Stereo Matching
Xiaoqing YE Jiamao LI Han WANG Xiaolin ZHANG
IEICE TRANSACTIONS on Information and Systems
Publication Date: 2017/12/01
Online ISSN: 1745-1361
Type of Manuscript: LETTER
Category: Image Recognition, Computer Vision
stereo matching, convolutional neural network, patch-based, occlusion disambiguation,
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Accurate stereo matching remains a challenging problem in case of weakly-textured areas, discontinuities and occlusions. In this letter, a novel stereo matching method, consisting of leveraging feature ensemble network to compute matching cost, error detection network to predict outliers and priority-based occlusion disambiguation for refinement, is presented. Experiments on the Middlebury benchmark demonstrate that the proposed method yields competitive results against the state-of-the-art algorithms.