Thumbnail
Access Restriction
Open

Author Prokos, A. ♦ Kalisperakis, I. ♦ Petsa, E. ♦ Karras, G.
Source CiteSeerX
Content type Text
File Format PDF
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Description Automation of camera calibration is facilitated by recording coded 2D patterns. Our toolbox for automatic camera calibration using images of simple chess-board patterns is freely available on the Internet. But it is unsuitable for stereo-cameras whose calibration im-plies recovering camera geometry and their true-to-scale relative orientation. In contrast to all reported methods requiring additional specific coding to establish an object space coordinate system, a toolbox for automatic stereo-camera calibration relying on ordinary chess-board patterns is presented here. First, the camera calibration algorithm is applied to all image pairs of the pattern to extract nodes of known spacing, order them in rows and columns, and estimate two independent camera parameter sets. The actual node cor-respondences on stereo-pairs remain unknown. Image pairs of a textured 3D scene are exploited for finding the fundamental matrix of the stereo-camera by applying RANSAC to point matches established with the SIFT algorithm. A node is then selected near the centre of the left image; its match on the right image is assumed as the node closest to the corresponding epipolar line. This yields matches for all nodes (since these have already been ordered), which should also satisfy the 2D epipolar geometry. Measures for avoiding mis-matching are taken. With automatically estimated initial orientation values, a bundle adjustment is performed constraining all pairs on a common (scaled) relative orientation. Ambiguities regarding the actual exterior orientations of the stereo-camera with respect to the pattern are irrelevant. Results from this automatic method show typical precisions not above pixels for 640x480 web cameras.
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research
Education Level UG and PG ♦ Career/Technical Study
Learning Resource Type Article
Publisher Date 2012-01-01
Publisher Institution International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol. XXXVIII, Part 5