DocumentCode
2615879
Title
Temporal surface reconstruction
Author
Heel, Joachim
Author_Institution
Artificial Intelligence Lab., MIT, Cambridge, MA, USA
fYear
1991
fDate
3-6 Jun 1991
Firstpage
607
Lastpage
612
Abstract
An approach which allows an arbitrary structure estimation to be embedded into a recursive estimation process that incrementally improves a structure estimate with every new frame that becomes available is discussed. The approach is based on Bayesian estimation theory and the Kalman filter. The authors demonstrate how it may be applied to such domains as depth from motion and depth from shading
Keywords
Kalman filters; computer vision; Bayesian estimation theory; Kalman filter; depth from motion; depth from shading; recursive estimation process; structure estimate; temporal surface reconstruction; Artificial intelligence; Contracts; Image reconstruction; Kalman filters; Layout; Motion estimation; Recursive estimation; Stereo image processing; Surface reconstruction; Uncertainty;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Vision and Pattern Recognition, 1991. Proceedings CVPR '91., IEEE Computer Society Conference on
Conference_Location
Maui, HI
ISSN
1063-6919
Print_ISBN
0-8186-2148-6
Type
conf
DOI
10.1109/CVPR.1991.139761
Filename
139761
Link To Document