Using vanishing points for camera calibration
International Journal of Computer Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence - Special issue on interpretation of 3-D scenes—part II
Active intrinsic calibration using vanishing points
Pattern Recognition Letters
Multiple view geometry in computer visiond
Multiple view geometry in computer visiond
Paracatadioptric Camera Calibration
IEEE Transactions on Pattern Analysis and Machine Intelligence
Catadioptric Omnidirectional Camera
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Equi-areal Catadioptric Sensors
OMNIVIS '02 Proceedings of the Third Workshop on Omnidirectional Vision
Constant Resolution Omnidirectional Cameras
OMNIVIS '02 Proceedings of the Third Workshop on Omnidirectional Vision
Catadioptric Camera Calibration Using Geometric Invariants
IEEE Transactions on Pattern Analysis and Machine Intelligence
The Raxel Imaging Model and Ray-Based Calibration
International Journal of Computer Vision
Using Points at Infinity for Parameter Decoupling in Camera Calibration
IEEE Transactions on Pattern Analysis and Machine Intelligence
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This paper describes a method of mirror localization to calibrate a catadioptric imaging system. While the calibration of a catadioptric system includes the estimation of various parameters, we focus on the localization of the mirror. The proposed method estimates the position of the mirror by observing pairs of parallel lights, which are projected from various directions. Although some earlier methods for calibrating catadioptric systems assume that the system is single viewpoint, which is a strong restriction on the position and shape of the mirror, our method does not restrict the position and shape of the mirror. Since the constraint used by the proposed method is that the relative angle of two parallel lights is constant with respect to the rigid transformation of the imaging system, we can omit both the translation and rotation between the camera and calibration objects from the parameters to be estimated. Therefore, the estimation of the mirror position by the proposed method is independent of the extrinsic parameters of a camera. We compute the error between the model of the mirror and the measurements, and then estimate the position of the mirror by minimizing this error. We test our method using both simulation and real experiments, and evaluate the accuracy thereof.