A theory of self-calibration of a moving camera
International Journal of Computer Vision
A Flexible New Technique for Camera Calibration
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms
SMBV '01 Proceedings of the IEEE Workshop on Stereo and Multi-Baseline Vision (SMBV'01)
Plane-based Calibration Algorithm for Multi-camera Systems via Factorization of Homography Matrices
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
A convenient multicamera self-calibration for virtual environments
Presence: Teleoperators and Virtual Environments
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This paper presents an approach to intrinsic and extrinsic camera parameter calibration from a series of photographs or from video. For the reliable and accurate estimation of camera parameters it is common to use specially designed calibration patterns. However, using a single pattern, a globally consistent calibration is only possible from positions and viewing directions from where this single pattern is visible. To overcome this problem, the presented approach uses multiple coded patterns that can be distributed over a large area. A connection graph representing visible patterns in multiple views is generated, which is used to estimate globally consistent camera parameters for the complete scene. The approach is evaluated on synthetic and real-world ground truth examples. Furthermore, the approach is applied to calibrate the stereocameras of a robotic head on a moving platform.