DocumentCode :
2479377
Title :
Visual planes-based simultaneous localization and model refinement for augmented reality
Author :
Servant, Fabien ; Marchand, Eric ; Houlier, Pascal ; Marchal, Isabelle
Author_Institution :
Orange Labs., INRIA, Orange, CA
fYear :
2008
fDate :
8-11 Dec. 2008
Firstpage :
1
Lastpage :
4
Abstract :
This paper presents a method for camera pose tracking that uses a partial knowledge about the scene. The method is based on monocular vision simultaneous localization and mapping (SLAM). With respect to classical SLAM implementations, this approach uses previously known information about the environment (rough map of the walls) and profits from the various available databases and blueprints to constraint the problem. This method considers that the tracked image patches belong to known planes (with some uncertainty in their localization) and that SLAM map can be represented by associations of cameras and planes. In this paper, we propose an adapted SLAM implementation and detail the considered models. We show that this method gives good results for a real sequence with complex motion for augmented reality (AR) application.
Keywords :
SLAM (robots); augmented reality; pose estimation; SLAM; augmented reality; camera pose tracking; image patches; monocular vision simultaneous localization and mapping; Acceleration; Additive noise; Augmented reality; Cameras; Image databases; Layout; Motion estimation; Predictive models; Simultaneous localization and mapping; Uncertainty;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition, 2008. ICPR 2008. 19th International Conference on
Conference_Location :
Tampa, FL
ISSN :
1051-4651
Print_ISBN :
978-1-4244-2174-9
Electronic_ISBN :
1051-4651
Type :
conf
DOI :
10.1109/ICPR.2008.4761313
Filename :
4761313
Link To Document :
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