Volumetric reconstruction of objects and scenes using range images

This paper reviews volumetric methods for fusing sets of range images to cr eate 3D models of objects or scenes. It also presents a new reconstruction method, which is a hybrid that combines several desirable aspects of techni ques discussed in the literature. The proposed reconstruction method projec ts each point, or voxel, within a volumetric grid back onto a collection of range images. Each voxel value represents the degree of certainty that the point is inside the sensed object. The certainty value is a function of th e distance from the grid point to the range image, as well as the sensor's noise characteristics. The super-Bayesian combination formula is used to fu se the data created from the individual range images into an overall volume tric grid. We obtain the object model by extracting an isosurface from the volumetric data using a version of the marching cubes algorithm. Results ar e shown from simulations and real range finders. (C) 1999 Academic Press.