Using Edge Position Difference and Pixel Correlation for Aligning Stereo-Camera Generated 3D Scans

Abstract

Projection of a textured 3D scan, with a fixed scale, will spatially align with the 2D image of the scanned scene only at an unique pose of the scan. If misaligned, the true 3D alignment can be estimated using information from a 2D-2D registration process that minimizes an appropriate error criteria by penalizing mismatch between the overlapping images. Scan data from complicated real-world scenes poses a challenging registration problem due to the tendency of the optimization procedure to become trapped in local minima. In addition, the 3D scan from a stereo camera is of very highresolution and shows mild geometrical distortion adding to the difficulty. This work presents a new registration process using a similarity measure named Edge Position Difference (EPD) combined with a pixel based correlation similarity measure. Together, the technique is able to show consistent and robust 3D-2D registration performance using stereo data, showcasing the potential for extending the technique for practical large scale mapping applications.