Abstract :
Helmholtz stereopsis is a surface reconstruction method that exploits reciprocity for the recovery of 3D shape without an assumed BRDF model, and it has been shown to yield high quality results when the cameras and light sources are carefully calibrated. In many practical cases, however, accurate off-line calibration is difficult (or impossible) to achieve. We address this issue by exploring widebaseline matching in Helmholtz stereo images. We identify two classes of local image interest regions (‘features’) that can be reliably detected and matched between views in a Helmholtz stereo dataset; and by exploiting reciprocity, we show how these regions can be used to recover both geometric and radiometric calibration information. When used in conjunction with existing methods for dense reconstruction, this provides an automated shape recovery pipeline that operates independent of reflectance and does not require the acquisition of additional calibration images off-line.
