The authors propose a scheme to generate the volume/surface octree structure from range data. The scheme is similar to that of the quadtree generation algorithm. However, in this case, each node in the quadtree is a binary tree corresponding to a range data point. Consequently, the octree of the viewed object can be generated efficiently by merging the neighboring binary trees recursively. Surface normals can be computed directly from the range image. They are encoded into associated binary trees and subsequently propagated to the corresponding octree nodes during the merging process. Since 3-D information of the viewed object is available in each range image, the proposed scheme is capable of capturing the concave structures in objects, which cannot be detected from intensity model construction. Furthermore, since the algorithms developed in this research are essentially recursive tree traversal procedures, they are suitable for parallel implementation.>