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

Many low level visual computation problems such as focus, stereo, etc. can be formulated as problems of extracting one or more parameters of a non-stationary transformation between two images. Because of the non-stationary nature, finite-width windows are widely used in various algorithms to extract spatially local information from images. While the choice of window width has a very profound impact on the quality of results of algorithms, there has been no quantitative way to measure or eliminate the negative effects of finite width windows. To address this problem, we introduce a new set of filters, moment filters. Due to their recursiveness in the Fourier and spatial domains, these filters allow the effects of finite-width windows and fore-shortening to be explicitly analyzed and eliminated.

Notes

Text Reference

Yalin Xiong and Steven Shafer, "Moment Filters for High Precision Computation of Focus and Stereo," IEEE/RSJ International Conference on Intelligent Robots and Systems,'Human Robot Interaction and Cooperative Robots', August, 1995, pp. 108 - 113.

BibTeX Reference

@inproceedings{Xiong_1995_1797,
   author = "Yalin Xiong and Steven Shafer",
   title = "Moment Filters for High Precision Computation of Focus and Stereo",
   booktitle = "IEEE/RSJ International Conference on Intelligent Robots and Systems,'Human Robot Interaction and Cooperative Robots'",
   pages = "108 - 113",
   month = "August",
   year = "1995",
}

The Robotics Institute

Menu