New Algorithms for Feature-Based 2d and 3d Registration

VASC Seminar (Monday, June 23, 3:30pm-4:30pm, NSH 1507)

Charles V. Stewart
Rensselaer Polytechnic Institute and DualAlign, LLC

Abstract
This talk presents a series of algorithms for feature-based registration. The Dual-Bootstrap approach to registration "grows" inter-image transformations by starting with single-keypoint matching in small image regions. It has been used to develop highly-successful algorithms for 2d-to-2d image registration, 3d-to-3d LiDAR scan registration, and the 3d-to-2d problem of determining the location of a camera with respect to a 3d model. The Dual-Bootstrap is now undergoing commercial development for a wide-variety of applications. More recently, the Location Registration and Recognition (LRR) algorithm has been developed as an aid to longitudinal diagnosis and treatment monitoring, particularly for lung cancer. Rather than applying deformable registration, clinical regions of interest in one CT scan (such as small volumes surrounding nodules) are automatically recognized and aligned in a second CT scan. Like the Dual-Bootstrap, LRR uses a combination of keypoint indexing, (local) feature-based refinement, and learned decision criteria. LRR works at near interactive speeds and is (slightly) more accurate than the best current deformable registration technique.

Speaker
Charles V. Stewart is a professor in the Department of Computer Science, Rensselaer Polytechnic Institute, Troy, New York. He has done sabbaticals at the GE Center for Research and Development in Niskayuna, New York, and at the Johns Hopkins University. In 1999, together with Ali Can and Badrinath Roysam, he received the Best Paper Award at the IEEE Conference on Computer Vision and Pattern Recognition (CVPR). In 2007, he founded DualAlign LLC, where he is currently working as chief scientist while on leave from Rensselaer.

RPIs Computer Vision group