Camera calibration with active phase target: improvement on feature detection and optimization

Abstract

The calibration of camera with intrinsic and extrinsic parameters is a procedure of significance in current imaging-based optical metrology. Improvement at two aspects, feature detection and overall optimization, are investigated here by using an active phase target and statistically constrained bundle adjustment (SCBA). From the observations in experiment and simulation, the feature detection can be enhanced by "virtual defocusing" and windowed polynomial fitting if sinusoidal fringe patterns are used as the active phase target. SCBA can be applied to avoid the difficult measurement of the active target. As a typical calibration result in our experiment, the root mean square of reprojection error can be reduced to 0.0067 pixels with the proposed method.