Calibration of a camera–projector monochromatic system

Abstract

Camera-projector systems are increasingly being used in many different applications, including object reconstruction. In recent years, a number of approaches have been proposed to calibrate such devices; in this paper a calibration method is presented which can be used with monochromatic systems. The method is based on open-source code, makes use of planar calibration patterns, is fully automatic, easy to use and fast. Additionally, no initial information regarding the camera interior orientation is needed, and both sensors (camera and projector) are fully calibrated during the process. The method is validated by a series of tests, where root mean square errors (RMSEs) in image space are kept below 1 pixel. Finally, the applicability of the method is demonstrated by implementing two different strategies to automatically reconstruct objects.

A Multi-Projector Calibration Method for Virtual Reality Simulators with Analytically Defined Screens

“…On the other hand, the tangential and radial distortion coefficients are computed following the method described in [32]. The equations used in OpenCV for correcting radial distortion are shown in Equations (7) and (8), where k 1 , k 2 and k 3 are the computed radial distortion coefficients. The tangential distortion is corrected via Equations (9) and (10), where p 1 and p 2 are the computed tangential distortion coefficients.…”

“…Many of these developments use chessboards-based planar references alone or with a combination of other planar surfaces to automatically measure 2D points (i.e., image points) and establish point correspondences [8][9][10][11][12][13][14]. Other authors use augmented reality markers to establish such correspondences or other kind of self-designed planar markers [15][16][17][18].…”

“…Many works on projector or multi-projector displays are based on planar surfaces [2][3][4][5][6][7][8], for which automated geometric correction and alignment is simplified through the use of planar homographies between the planar screen, the projector frame buffers, and the images of one or more cameras observing the screen. Many of these developments use chessboards-based planar references alone or with a combination of other planar surfaces to automatically measure 2D points (i.e., image points) and establish point correspondences [8][9][10][11][12][13][14].…”