A maximum likelihood stereo algorithm
Computer Vision and Image Understanding
The Geometry of Multiple Images: The Laws That Govern The Formation of Images of A Scene and Some of Their Applications
A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms
International Journal of Computer Vision
A Computational Framework for Determining Stereo Correspondence from a Set of Linear Spatial Filters
ECCV '92 Proceedings of the Second European Conference on Computer Vision
Stereo Matching Using Belief Propagation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Sampling the Disparity Space Image
IEEE Transactions on Pattern Analysis and Machine Intelligence
Journal of Mathematical Imaging and Vision
How Accurate Can Block Matches Be in Stereo Vision?
SIAM Journal on Imaging Sciences
Combining monocular geometric cues with traditional stereo cues for consumer camera stereo
ECCV'12 Proceedings of the 12th international conference on Computer Vision - Volume 2
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This paper presents a study of small baseline stereovision. It is generally admitted that because of the finite resolution of images, getting a good precision in depth from stereovision demands a large angle between the views. In this paper, we show that under simple and feasible hypotheses, small baseline stereovision can be rehabilitated and even favoured. The main hypothesis is that the images should be band limited, in order to achieve sub-pixel precisions in the matching process. This assumption is not satisfied for common stereo pairs. Yet, this becomes realistic for recent spatial or aerian acquisition devices. In this context, block-matching methods, which had become somewhat obsolete for large baseline stereovision, regain their relevance. A multi-scale algorithm dedicated to small baseline stereovision is described along with experiments on small angle stereo pairs at the end of the paper.