A Correspondence Search Technique for Geometric Correction of Projected Images

Abstract

This paper presents a technique for correspondence search between projector and camera images using SIFT (Scale-Invariant Feature Transform) and POC (Phase-Only Correlation). The correspondence search is a key task for camera-based geometric correction of projected imagery. In conventional methods, the correspondence is obtained by projecting the structured light on a projector screen. This paper proposes a geometric correction technique where we use only one snapshot of ordinary video sequences to find projector-camera correspondence. We adopt (i) SIFT-based feature matching to estimate an approximate homography between projector and camera images with a limited number of corresponding points and (ii) POC-based dense sub-pixel correspondence search to adjust precise position of corresponding points. Through a set of experiments, we demonstrate that the proposed technique achieves high-accuracy geometric correction, even if significant brightness change is observed between the original video content to be projected and the real projector image captured by a camera.