Publication Date


Document Type


Committee Members

Arthur Goshtasby (Committee Chair), Lang Hong (Committee Member), Jack Jean (Committee Member), Kathleen Robinette (Committee Member), Thomas Wischoll (Committee Member)

Degree Name

Doctor of Philosophy (PhD)


A method to automatically characterize and identify 3-D range scans based on intrinsic landmarks is presented. Intrinsic landmarks represent locally unique, intrinsic properties of a scanned surface, regardless of scale or rotation. The number, location, and characteristics of landmarks are used to characterize the scanned models. This method contains a selection process to identify stable, intrinsic landmarks for range scans as well as the identification of those scans. The selection process requires no user interaction or surface assumptions. It uses the principal curvatures at the range points to select the landmarks. First, a large number of landmarks are generated by fitting a bi-cubic polynomial surface to points surrounding each range point and calculating the principal curvatures at the range point. Points of locally extremum principal curvature are then considered candidate landmarks. Using a random sample and consensus (RANSAC) algorithm, candidate landmarks that match with landmarks in other scans of the same subject are selected as final, stable landmarks.

Our main goal is to provide a means to characterize models in a range data base. With several scans of each subject available in the data base, a number of stable landmarks are determined for each subject. The locations and characteristics of the landmarks are used to describe a subject and distinguish it from other subjects. The main contribution of this work is considered to be the selection of unique and stable landmarks in a range scan and generation of a descriptor for each landmark that characterizes the intrinsic properties of the surface in the neighborhood of the landmark. The effectiveness of the method is presented through the successful identification of processed subjects and characterization of new subjects.

Page Count


Department or Program

Department of Computer Science and Engineering

Year Degree Awarded