Kalman Filter-based Algorithms for Estimating Depth from Image Sequences

by: Larry Matthies, Takeo Kanade, Richard Szeliski

International Journal of Computer Vision, Vol. 3, No. 3. (1989), pp. 209-238.

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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...

@article{citeulike:2250143, 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...}, author = {Matthies, Larry and Kanade, Takeo and Szeliski, Richard }, citeulike-article-id = {2250143}, journal = {International Journal of Computer Vision}, keywords = {filter, kalman, monocular, scaling, scene, vision}, number = {3}, pages = {209--238}, posted-at = {2008-01-18 08:53:14}, priority = {5}, title = {Kalman Filter-based Algorithms for Estimating Depth from Image Sequences}, url = {http://citeseer.ist.psu.edu/matthies89kalman.html}, volume = {3}, year = {1989} }

RIS record

TY - JOUR ID - citeulike:2250143 L3 - citeulike-article-id:2250143 TI - Kalman Filter-based Algorithms for Estimating Depth from Image Sequences JF - International Journal of Computer Vision VL - 3 IS - 3 SP - 209 EP - 238 N2 - 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... KW - filter KW - kalman KW - monocular KW - scaling KW - scene KW - vision AU - Matthies, Larry AU - Kanade, Takeo AU - Szeliski, Richard PY - 1989/// UR - http://citeseer.ist.psu.edu/matthies89kalman.html ER -

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