Self-calibration from multiple views with a rotating camera
ECCV '94 Proceedings of the third European conference on Computer vision (vol. 1)
ViRoom - Low Cost Synchronized Multicamera System and Its Self-calibration
Proceedings of the 24th DAGM Symposium on Pattern Recognition
A Four-step Camera Calibration Procedure with Implicit Image Correction
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Multiple View Geometry in Computer Vision
Multiple View Geometry in Computer Vision
An Efficient Solution to the Five-Point Relative Pose Problem
IEEE Transactions on Pattern Analysis and Machine Intelligence
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Self-calibration with partially known rotations
Proceedings of the 29th DAGM conference on Pattern recognition
Intrinsic and extrinsic active self-calibration of multi-camera systems
Machine Vision and Applications
| Hi-index | 0.01 |
We present a method for actively calibrating a multicamera system consisting of pan-tilt zoom cameras. After a coarse initial calibration, we determine the probability of each relative pose using a probability distribution based on the camera images. The relative poses are optimized by rotating and zooming each camera pair in a way that significantly simplifies the problem of extracting correct point correspondences. In a final step we use active camera control, the optimized relative poses, and their probabilities to calibrate the complete multi-camera system with a minimal number of relative poses. During this process we estimate the translation scales in a camera triangle using only two of the three relative poses and no point correspondences. Quantitative experiments on real data outline the robustness and accuracy of our approach.