James McGreger
Computer Science
M.S. 1998

Registration of Laser-Range Images

Research Objectives:
Being able to accurately model a 3D scene is important to many applications. Three major steps are involved in the process: (1) data acquisition from multiple viewpoints,
(2) view registration, and (3) view integration or data fusion. Our focus is on view registration, which is the problem of determining the rigid transformation that describes the motion of the camera platform between two or more views. While a completely data-driven method is the goal, semi-automatic methods requiring minimal user interaction are also being investigated.

Methodology and Results:
Several point-based methods have been proposed for fine-tuning a given motion estimate. One exemple is the so-called Iterative Closest Point (ICP) algorithm, which is widely used and constitutes a generic enough framework to describe other related algorithms. Starting from the given motion estimate, point correspondences are established and fed to a least-squares solver that produces a new motion estimate. The process continues until convergence or for a predetermined number of iterations. Different versions of the ICP algorithm are studied to determine their robustness and possible application to real data. Sometimes an approximate motion estimate is not available, e.g. when the camera platform is moved around manually. Under such circumstances, it may be impossible to establish good point correspondences, even via user interaction. To overcome this problem, we take a plane-based approach. The underlying philosophy is that planar surface patches are typically plentiful in man-made scenes, e.g. buildings; they can be detected and modeled robustly via appropriate segmentation and least-squares fitting, and a user can then easily identify correspondences. The one stipulation is that the set of planes selected in each view must span a 3D space. The approach can easily be extended to use other data models such as generalized cylinders.

This work was conducted by James McGreger while at IRIS lab under the supervision of J. Gregor. This work was supported by DOE's University Research Program in Robotics under grant DOE-DE-FG02-86NE37968.