The Robotics Institute

Carnegie Mellon Robotics Institute

Copyright notice: This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. These works may not be reposted without the explicit permission of the copyright holder.

Abstract

This paper describes the design and implementation of an algorithm for improving the performance of stereo vision in environments presenting repetitive patterns or regions with relatively weak texture. The proposed algorithm makes use of the common assumption that the disparities corresponding to continuous surfaces in the world vary smoothly; we are using this assumption to alleviate the correspondence problem for pixels that cannot be reliably matched by the stereo algorithm. Our approach can be described as a reliability based filtering of the disparity image followed by a recursive propagation step. It can be applied to the output of almost any "standard" stereo algorithm with minimal modifications, and is computationally efficient.

Keywords

indoor stereo vision

Notes

Number of pages: 7

Note: This publication is based on work performed at LAAS-CNRS in Toulouse, France (June-August 2001).

Text Reference

Cristian Dima and Simon Lacroix, "Using Multiple Disparity Hypotheses for Improved Indoor Stereo," International Conference on Robotics and Automation, May, 2002, pp. 3347 - 3353.

BibTeX Reference

@inproceedings{Dima_2002_4682,
   author = "Cristian Dima and Simon Lacroix",
   title = "Using Multiple Disparity Hypotheses for Improved Indoor Stereo",
   booktitle = "International Conference on Robotics and Automation",
   pages = "3347 - 3353",
   publisher = "IEEE",
   month = "May",
   year = "2002",
   volume = "4",
   Notes = "This publication is based on work performed at LAAS-CNRS in Toulouse, France (June-August 2001)."
}

The Robotics Institute

Menu