DocumentCode :
2689513
Title :
A unified factorization algorithm for points, line segments and planes with uncertainty models
Author :
Morris, Daniel D. ; Kanade, Takeo
Author_Institution :
Robotics Inst., Carnegie Mellon Univ., Pittsburgh, PA, USA
fYear :
1998
fDate :
4-7 Jan 1998
Firstpage :
696
Lastpage :
702
Abstract :
In this paper we present a unified factorization algorithm for recovering structure and motion from image sequences by using point features, line segments and planes. This new formulation is based on directional uncertainty model for features. Points and line segments are both described by the same probabilistic models and so can be recovered in the same way. Prior information on the coplanarity of features is shown to fit naturally into the new factorization formulation and provides additional constraints for the shape recovery. This formulation leads to a weighted least squares motion and shape recovery problem which is solved by an efficient quasi-linear algorithm. The statistical uncertainty model also enables us to recover uncertainty estimates for the reconstructed three dimensional feature locations
Keywords :
computer vision; image segmentation; image sequences; coplanarity; directional uncertainty model; image sequences; line segments; planes; point features; points; probabilistic models; quasi-linear algorithm; shape recovery; statistical uncertainty model; three dimensional feature locations; uncertainty estimates; uncertainty models; unified factorization algorithm; weighted least squares motion; Cameras; Image reconstruction; Image sequences; Layout; Least squares methods; Measurement uncertainty; Nonlinear distortion; Robots; Shape measurement; Solid modeling;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Vision, 1998. Sixth International Conference on
Conference_Location :
Bombay
Print_ISBN :
81-7319-221-9
Type :
conf
DOI :
10.1109/ICCV.1998.710793
Filename :
710793
Link To Document :
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