Metrology in uncalibrated images given one vanishing point

In this paper, we describe how 3D Euclidean measurements can be made in a pair of uncalibrated images, when only minimal geometric information are available in the image planes. This minimal information consists of a line in a reference plane, and the vanishing point orthogonal to it. Given such limited information, we show that the length ratio of two objects perpendicular to the reference plane can be expressed as a function of the camera intrinsic parameters. Assuming that the camera intrinsic parameters remain invariant between two views, we perform Euclidean metric measurements directly in the perspective images.

[1]  Paulo R. S. Mendonça,et al.  Camera Calibration from Surfaces of Revolution , 2003, IEEE Trans. Pattern Anal. Mach. Intell..

[2]  Andrew Zisserman,et al.  Combining scene and auto-calibration constraints , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.

[3]  Bernhard P. Wrobel,et al.  Multiple View Geometry in Computer Vision , 2001 .

[4]  Ian D. Reid,et al.  Single View Metrology , 2000, International Journal of Computer Vision.

[5]  Olivier D. Faugeras,et al.  A theory of self-calibration of a moving camera , 1992, International Journal of Computer Vision.

[6]  B. Caprile,et al.  Using vanishing points for camera calibration , 1990, International Journal of Computer Vision.

[7]  Ramakant Nevatia,et al.  Self-calibration of a camera from video of a walking human , 2002, Object recognition supported by user interaction for service robots.

[8]  Roberto Cipolla,et al.  Camera Calibration from Vanishing Points in Image of Architectural Scenes , 1999, BMVC.