Calibration camera

Tsai, R.Y. A versatile camera calibration technique for high-accuracy 3D machine vision meterology using off-the-shell tv cameras and lenses. IEEE. 1.Robotics Automation, Vol. RA-3(4),August 1988, pp. 323-344. 

Finlayson GD and Drew MS 2001 4-sensor camera calibration for image representation invariant to shading, shadows, lighting, and specularities. Proceedings of the 8th IEEE International Conference on Computer Vision, Volume 2, Vancouver, Canada, July 9-12, 2001, pp. 473-480. 

The camera calibration, in our case, is accomplished by a least-squares method to determine the relative position and orientation of two cameras from a set of matched points. For more detail of camera calibration see Slama (1980). 

Huang and Harley (1989) have developed a calibration method for this system by using an imaginary 3-D field from a 2-D field observed on the image plane. Z-coordinates in this method have about the same value. Therefore, a camera calibration in this system becomes a calibration problem in a 2-D field. Tsai (1986) has developed a self-calibration method from a 2-D field for the machine vision. 

Brown D.C. (1971) Close-Range Camera Calibration. Photogrammetric Engineering, pp 855-866. 

Faugeras O.D., Toscani G. (1987) Camera Calibration for 3-D Computer Vision. 

Huang Y.D., Harley I. (1989) Camera Calibration without a Control Field -a New Method, Optical 3-D Measurement Techniques, pp 49-56. 

Tsai R.Y. (1986) An Efficient and Accurate Camera Calibration Technique for 3-D Machine Vision. IEEE pp 364-374. 

W. Qi, F. Li, L. Zhenzhong, Review on camera calibration IEEE, in Chinese Control and Decesion Conference, 2010, pp 3354-3358... 

J. Weng, P. Cohen, M. Hemiou, Camera calibration with distortion models and accuracy evaluation, IEEE Transactions on pattern analysis and machine intelligence 14 (1992) 965-980. 

H. Luo, L. Zhu, H. Ding, Camera calibration with coplanar calibration board near parallel to the... 

D. Samper, J. Santolaria, A C. Majarena, J.J. Aguilar, Comprehensive Simulation Software for Teaching Camera Calibration by a Constructivist Methodology, Measurement, 43 (2010) 618-630. 

Camera Calibration. Each camera must be calibrated before it can contribute to locating a target in object-space. Camera calibration defines a mapping from three-dimensional object-space into the two-dimensional u, v coordinates of the camera. This mapping is expressed in Eq. (5.2) in terms of homogeneous coordinates ... 

This discussion on camera calibration is not meant to be comprehensive. However, it does provide the basic background for understanding how and why cameras ate calibrated. Additional terms can be added to the basic 11-parameter DLT model to correct for symmetrical and asymmetrical lens distortions. These errors can be treated, in part, during camera calibration, and may also be accounted for by using lens correction maps provided by the manufacturer. 

In a typical imaging situation, the camera may have several degrees of freedom, such as translation, pan, and tilt. Also, more than one camera maybe imaging the same scene from different points. In this case, it is convenient to adopt a world coordinate system in reference to which the scene coordinates and camera coordinates are defined. In this situation, however, the imaging equations become more cumbersome and we refer you to the references at the end of this chapter for a more complete discussion of imaging geometry including camera calibration. 

Figure 4.7 Schematic of navigated endoscopic tracking using (a) extrinsic and (b) intrinsic (vision) tracking systems. The ability to fuse ultrasound (US) into video depends on the accurate estimation of the transition Tus- The local coordinate system of the extrinsic tracking system (often magnetic) is used as the world coordinate system (W), where the WTDRB denotes the tracker transformations. DRB USTUS denotes the US calibration matrix and VTDRB V denotes the camera calibration.

By applying the projection matrix P to the environment model M, the lane data is projected into the rear-view camera image. The matrix P is built up of the extrinsic (3D translation (y) and roll yaw (il/cX pitch (9c), angles), and intrinsic (center of distortion uq, vq and focal length ) camera calibration data (see Eq. 4). 

With the precise vehicle contour available, the ground maik can be assumed to be the undermost pixel of the mask. Based on the flat world assumption (z = 0) and the intrinsic and extrinsic camera calibration (see Sect. 1.2), the 3D coordinates xg,yg, Zg) of the ground mark in image space (m, Vg) are calculated ... 

Tsai, R.Y., "An efficient and accurate camera calibration technique for 3-D machine vision," Proc. IEEE Conference on Computer Vision and Pattern Recognition, Miami, Florida, pp.364-374,1986. 

D. C. Brown. Close-range camera calibration. Photogrammetric Engineering, 37(8) 855-866, 1971. 

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