Three-dimensional shape model reconstruction from multiple view range images and color images

Recently, there is an increasing interest in capturing 3D models of real objects. The range scanner can acquire high quality shape data of the object, but the texture image for surface rendering obtained by the scanner is not generally high resolution and high quality. High-resolution color images at different position are generally taken in addition to the range data so that more realistic images can be rendered from the captured 3D model using such high quality textures. We propose the method of modeling high quality 3D model in shape and appearance by aligning multiple view range images obtained by a range scanner and multiple view color images taken by a digital camera around the object. Color images used as textures are calibrated by Tsai's method, in which lens distortion is also calibrated. On the other hand, a surface model of the object is created by registering and integrating range data sets taken from multiple directions. For registration, we use color ICP (Iterative Closest Point) algorithm that aligns two surfaces using color images and surface shape of the object. For integration, we build voxel model from range images and then detect polygons by Marching Cubes algorithm. We apply textures of high-resolution images to the surfaces by blending, and finally reconstruct realistic 3D model concerned with shape and appearance.