DocumentCode :
3485210
Title :
Robust 3D pose estimation from multiple video cameras
Author :
Chen, Chong ; Schonfeld, Dan
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Illinois at Chicago, Chicago, IL, USA
fYear :
2009
fDate :
7-10 Nov. 2009
Firstpage :
541
Lastpage :
544
Abstract :
In this paper, we introduce a method to estimate the object´s pose from multiple video cameras. We derive a centralized solution to pose estimation from multiple video cameras by solving a general matrix equation. Moreover, we provide an equivalent distributed solution to the pose estimation problem based on the independent pose estimation obtained from each camera. We demonstrate that both methods generate superior estimates to the results obtained from any specific camera view. The resulting pose estimation technique is shown to be robust to occlusion and errors from specific camera views, and the computational complexity of the distributed solution grows linearly with the number of cameras. Furthermore, the proposed approach does not require feature matching among images from different camera views nor does it demand reconstruction of 3D points.
Keywords :
computational complexity; hidden feature removal; image sensors; matrix algebra; pose estimation; computational complexity; general matrix equation; multiple video cameras; occlusion; robust 3D pose estimation; Boosting; Cameras; Computational complexity; Equations; Image reconstruction; Image sequences; Motion estimation; Object detection; Robustness; Singular value decomposition; Distributed Estimation; Multiple Views; Pose Estimation; Sylvester´s Equation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Processing (ICIP), 2009 16th IEEE International Conference on
Conference_Location :
Cairo
ISSN :
1522-4880
Print_ISBN :
978-1-4244-5653-6
Electronic_ISBN :
1522-4880
Type :
conf
DOI :
10.1109/ICIP.2009.5413937
Filename :
5413937
Link To Document :
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