Title :
Multiview image registration using augmented Kalman filter
Author :
Xu, Zezhong ; Zhuang, Yanbin
Author_Institution :
Dept. of Comput. Inf. & Eng., Changzhou Inst. of Technol., Changzhou, China
Abstract :
Multiview image registration is widely used in computer vision applications. In this paper, an approach for multiview 3D image registration based on augmented Kalman filter is proposed by taking account of various uncertainties. The position and orientation of viewpoint are considered as system state. System augmentation model and system observation model are constructed. The position and orientation of each viewpoint is augmented and updated recursively. The global transformation parameters of image are computed with the state estimation of corresponding viewpoint. The proposed multiview image registration method can handle the uncertainty efficiently and the registration result is accurate and globally consistent. Some experimental results are provided to validate the performance of the proposed method.
Keywords :
Kalman filters; computer vision; image registration; state estimation; stereo image processing; uncertainty handling; augmented Kalman filter; computer vision; multiview 3D image registration; state estimation; system observation model; uncertainty handling; viewpoint orientation; viewpoint position; Computational modeling; Covariance matrix; Image registration; Kalman filters; State estimation; Three dimensional displays; Uncertainty; Augmented Kalman filter; Consistency; Image registration;
Conference_Titel :
Intelligent Control and Automation (WCICA), 2010 8th World Congress on
Conference_Location :
Jinan
Print_ISBN :
978-1-4244-6712-9
DOI :
10.1109/WCICA.2010.5554873