(Enter summary)
Abstract: Using known camera motion to estimate depth from image sequences is an important problem in robot vision. Many
applications of depth-from-motion, including navigation and manipulation, require algorithms that can estimate depth
in an on-line, incremental fashion. This requires a representation that records the uncertainty in depth estimates and
a mechanism that integrates new measurements with existing depth estimates to reduce the uncertainty over time.
Kalman filtering provides this... (Update)
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BibTeX entry: (Update)
L. Matthies, R. Szelinski, and T. Kanade. Kalman Filter-based Algorithms for Estimating Depth from Image Sequences. Int. J. Computer Vision, pages 2989--2994, 1989. http://citeseer.ist.psu.edu/matthies89kalman.html More
@article{ matthies89kalman,
author = "Larry Matthies and Takeo Kanade and Richard Szeliski",
title = "Kalman Filter-based Algorithms for Estimating Depth from Image Sequences",
journal = "International Journal of Computer Vision",
volume = "3",
number = "3",
pages = "209--238",
year = "1989",
url = "citeseer.ist.psu.edu/matthies89kalman.html" }
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