Range data registration using photometric features

• Published in: 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) Vol. 2; pp. 1140 - 1145 vol. 2
• Main Authors: Joon Kyu Seo, Sharp, G.C., Sang Wook Lee
• Format: Conference Proceeding
• Language: English
• Published: IEEE 2005
• Subjects: Computer vision; Data mining; Feature extraction; Hospitals; Iterative closest point algorithm; Layout; Oncology; Photometry; Shape; Surface texture
• DOI: 10.1109/CVPR.2005.289
• ISBN: 0769523722; 9780769523729
• ISSN: 1063-6919

This paper investigates the use of photometric features for the pair-wise registration of range images. Many artificial and natural objects exhibit abundant surface texture that may not be revealed in range data, and most structured light and laser range sensors are capable of capturing either grayscale or color photometric intensity in addition to range data. Nevertheless, the use of photometric features has not been widely investigated for range data registration, despite widespread research into local feature descriptors for object recognition in 2D photometric images. This paper addresses some of the problems that arise in using photometric features for range data registration, and presents a systematic method for their use. Potentially useful photometric features are detected on planar regions in 3D, and then reprojected to 2D to remove the perspective distortion. Then, a well-established 2D rotation- and brightness-invariant image feature descriptor is used for matching. Range data alignment is performed using a RANSAC algorithm, with verification performed in 3D. Experimental results demonstrate the effectiveness of this method.