Title :
Constrained self-calibration
Author :
Mendelsohn, Jeffrey ; Daniilidis, Kostas
Author_Institution :
GRASP Lab., Pennsylvania Univ., Philadelphia, PA, USA
Abstract :
This paper focuses on the estimation of the intrinsic camera parameters and the trajectory of the camera from an image sequence. Intrinsic camera calibration and pose estimation are the prerequisites for many applications involving navigation tasks, scene reconstruction, and merging of virtual and real environments. Proposed and evaluated is a technical solution to decrease the sensitivity of self-calibration by placing easily identifiable targets of known shape in the environment. The relative position of the targets need not be known a priori. Assuming an appropriate ratio of size to distance these targets resolve known ambiguities. Constraints on the target placement and the cameras´ motions are explored. The algorithm is extensively tested in a variety of real-world scenarios
Keywords :
calibration; image reconstruction; image sequences; parameter estimation; camera calibration; constrained self-calibration; easily identifiable targets; image sequence; intrinsic camera parameters estimation; pose estimation; scene reconstruction; Calibration; Cameras; Image reconstruction; Image sequences; Laboratories; Layout; Merging; Navigation; Shape; Testing;
Conference_Titel :
Computer Vision and Pattern Recognition, 1999. IEEE Computer Society Conference on.
Conference_Location :
Fort Collins, CO
Print_ISBN :
0-7695-0149-4
DOI :
10.1109/CVPR.1999.784974