Three-dimensional computer vision: a geometric viewpoint
Three-dimensional computer vision: a geometric viewpoint
A maximum likelihood stereo algorithm
Computer Vision and Image Understanding
Viewpoint Estimation in Three-Dimensional Images Taken with Perspective Range Sensors
IEEE Transactions on Pattern Analysis and Machine Intelligence
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
Parameter Estimation for MRF Stereo
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
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
| Hi-index | 0.00 |
In this paper a new method for reconstructing 3D scenes from stereo images is presented, as well as an algorithm for environment mapping, as an application of the previous method. In the reconstruction process a geometrical rectification filter is used to remove the conical perspective of the images. It is essential to recover the geometry of the scene (with real data of depth and volume) and to achieve a realistic appearance in 3D reconstructions. It also uses sub-pixel precision to solve the lack of information for distant objects. Finally, the method is applied to a mapping algorithm in order to show its usefulness.