Three-dimensional computer vision: a geometric viewpoint
Three-dimensional computer vision: a geometric viewpoint
A maximum likelihood stereo algorithm
Computer Vision and Image Understanding
Introductory Techniques for 3-D Computer Vision
Introductory Techniques for 3-D Computer Vision
Manhattan world: orientation and outlier detection by Bayesian inference
Neural Computation
Robust real-time lane and road detection in critical shadow conditions
ISCV '95 Proceedings of the International Symposium on Computer Vision
Multi-View Stereo via Volumetric Graph-Cuts
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
Three-dimensional mapping from stereo images with geometrical rectification
AMDO'06 Proceedings of the 4th international conference on Articulated Motion and Deformable Objects
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The reconstruction and mapping of real scenes is a crucial element in several fields such as robot navigation. Stereo vision can be a powerful solution. However the perspective effect arises, as well as other problems, when the reconstruction is tackled using depth maps obtained from stereo images. A new approach is proposed to avoid the perspective effect, based on a geometrical rectification using the vanishing point of the image. It also uses sub-pixel precision to solve the lack of information for distant objects. Finally, the method is applied to map a whole scene, introducing a cubic filter.