DocumentCode :
3572407
Title :
Robust Frame Registration for Multiple Camera Setups in Dynamic Scenes
Author :
Xu Zhao ; Zhong Zhou ; Ye Duan ; Wei Wu
Volume :
1
fYear :
2012
Firstpage :
373
Lastpage :
380
Abstract :
In this paper, we propose a novel method to register frames from multiple cameras into a consistent global scale. Assuming a moving object is observed in multiple camera setups, we use initial frames to create a global reference structure where the pose variation of each new frame is estimated using a RANSAC-based registration algorithm. We further combine the registration method with other state-of the-art techniques to build a high quality 3D reconstruction system with a smaller number of cameras than used by more traditional methods. Experimental results show that our method performs better and is more economical than the registration of separate monocular structures from motion methods. 3D reconstruction results on various challenging real world multi-camera video datasets also illustrate the feasibility and robustness of our method.
Keywords :
cameras; image motion analysis; image registration; statistical analysis; RANSAC-based registration algorithm; dynamic scenes; global reference structure; high quality 3D reconstruction system; moving object; multiple camera setups; pose variation; real-world multicamera video datasets; robust frame registration; separate monocular structures registration; Cameras; Image reconstruction; Registers; Solid modeling; Stereo image processing; Surface reconstruction; Three-dimensional displays; Bundle Adjustment; Frame Registration; Multiple Camera Setups;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Tools with Artificial Intelligence (ICTAI), 2012 IEEE 24th International Conference on
ISSN :
1082-3409
Print_ISBN :
978-1-4799-0227-9
Type :
conf
DOI :
10.1109/ICTAI.2012.58
Filename :
6495070
Link To Document :
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