Multiple Interpretations of the Shape and Motion of Objects from Two Perspective Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Using collineations to compute motion and structure in an uncalibrated image sequence
International Journal of Computer Vision
International Journal of Computer Vision
A Flexible New Technique for Camera Calibration
IEEE Transactions on Pattern Analysis and Machine Intelligence
Theory of Reconstruction from Image Motion
Theory of Reconstruction from Image Motion
Estimation of Relative Camera Positions for Uncalibrated Cameras
ECCV '92 Proceedings of the Second European Conference on Computer Vision
What can be seen in three dimensions with an uncalibrated stereo rig
ECCV '92 Proceedings of the Second European Conference on Computer Vision
A Stratified Approach to Metric Self-Calibration
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Comparison of Approaches to Egomotion Computation
CVPR '96 Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition (CVPR '96)
Scaled Euclidean 3D reconstruction based on externally uncalibrated cameras
ISCV '95 Proceedings of the International Symposium on Computer Vision
An Efficient Solution to the Five-Point Relative Pose Problem
IEEE Transactions on Pattern Analysis and Machine Intelligence
On structured light vision sensor calibration in a robot based 3D laser scanning system
ROBIO'09 Proceedings of the 2009 international conference on Robotics and biomimetics
Optimized particles for 3-D tracking
ICIRA'10 Proceedings of the Third international conference on Intelligent robotics and applications - Volume Part I
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Self-recalibration of the relative pose in a vision system plays a very important role in many applications and much research has been conducted on this issue over the years. However, most existing methods require information of some points in general three-dimensional positions for the calibration, which is hard to be met in many practical applications. In this paper, we present a new method for the self-recalibration of a structured light system by a single image in the presence of a planar surface in the scene. Assuming that the intrinsic parameters of the camera and the projector are known from initial calibration, we show that their relative position and orientation can be determined automatically from four projection correspondences between an image and a projection plane. In this method, analytical solutions are obtained from second order equations with a single variable and the optimization process is very fast. Another advantage is the enhanced robustness in implementation via the use of over constrained systems. Computer simulations and real data experiments are carried out to validate our method.