Simultaneous 2D images and 3D geometric model registration for texture mapping utilizing reflectance attribute

Abstract

Texture mapping on scanned objects, that is, the method to map current color images on a 3D geometric model measured by a range sensor, is a key technique of photometric modeling for virtual reality. Usually range and color images are obtained from different viewing positions, through two independent range and color sensors. Thus, in order to map those color images on the geometric model, it is necessary to determine relative relations between these two viewpoints. In this paper, we propose a new calibration method for the texture mapping; the method utilizes reflectance images and iterative pose estimation based on a robust M-estimator. Moreover, since a 2D texture image taken from one viewing point is a partial view of an object, several images must be mapped onto the object in order to cover the entire 3D geometric model. In this paper, we propose the new simultaneous registration technique of several images and geometric model based on 2D-3D edge correspondence and the epipolar constraint between images.