Rectified Reconstruction from Stereo Pairs and Robot Mapping

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.

[1]  José A. Castellanos,et al.  Mobile Robot Localization and Map Building , 1999 .

[2]  Rafael Molina-Carmona,et al.  Three-Dimensional Mapping from Stereo Images with Geometrical Rectification , 2006, AMDO.

[3]  O. Faugeras.  Three-dimensional computer vision: a geometric viewpoint , 1993 .

[4]  Gonzalo Pajares Martinsanz,et al.  Visión por computador: imágenes digitales y aplicaciones , 2001 .

[5]  Marc Pollefeys,et al.  Multi-view reconstruction using photo-consistency and exact silhouette constraints: a maximum-flow formulation , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.

[6]  Hans P. Moravec.  Robot spatial perception by stereoscopic vision and 3D evidence grids , 1996 .

[7]  Ingemar J. Cox,et al.  A Maximum Likelihood Stereo Algorithm , 1996, Comput. Vis. Image Underst..

[8]  James J. Little,et al.  Vision-based mobile robot localization and mapping using scale-invariant features , 2001, Proceedings 2001 ICRA. IEEE International Conference on Robotics and Automation (Cat. No.01CH37164).

[9]  Emanuele Trucco,et al.  Introductory techniques for 3-D computer vision , 1998 .

[10]  J. M. M. Montiel,et al.  Continuous mobile robot localization: vision vs. laser , 1999, Proceedings 1999 IEEE International Conference on Robotics and Automation (Cat. No.99CH36288C).

[11]  Roberto Cipolla,et al.  Multi-view stereo via volumetric graph-cuts , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[12]  Hong Bing-rong,et al.  Real-time acquisition of compact volumetric maps , 2006 .

[13]  Petia Radeva,et al.  Artificial Intelligence Research and Development , 2005 .

[14]  Rosana Satorre Cuerda,et al.  Disparity estimation in stereoscopic vision by simulated annealing , 2003 .

[15]  James M. Coughlan,et al.  Manhattan World: Orientation and Outlier Detection by Bayesian Inference , 2003, Neural Computation.

[16]  Alberto Broggi.  Robust real-time lane and road detection in critical shadow conditions , 1995, Proceedings of International Symposium on Computer Vision - ISCV.