A Method for Registration of 3-D Shapes
IEEE Transactions on Pattern Analysis and Machine Intelligence - Special issue on interpretation of 3-D scenes—part II
Object modelling by registration of multiple range images
Image and Vision Computing - Special issue: range image understanding
Using Spin Images for Efficient Object Recognition in Cluttered 3D Scenes
IEEE Transactions on Pattern Analysis and Machine Intelligence
ACM SIGGRAPH 2003 Papers
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Convergent Discrete Laplace-Beltrami Operators over Triangular Surfaces
GMP '04 Proceedings of the Geometric Modeling and Processing 2004
Scale & Affine Invariant Interest Point Detectors
International Journal of Computer Vision
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
3DIM '05 Proceedings of the Fifth International Conference on 3-D Digital Imaging and Modeling
Multi-Image Matching Using Multi-Scale Oriented Patches
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
A Performance Evaluation of Local Descriptors
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Comparison of Affine Region Detectors
International Journal of Computer Vision
Registration of combined range-intensity scans: Initialization through verification
Computer Vision and Image Understanding
Geodesic Distance-weighted Shape Vector Image Diffusion
IEEE Transactions on Visualization and Computer Graphics
Intrinsic Geometric Scale Space by Shape Diffusion
IEEE Transactions on Visualization and Computer Graphics
Keypoints and Local Descriptors of Scalar Functions on 2D Manifolds
International Journal of Computer Vision
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We present a new framework for detecting, describing, and matching keypoints in combined range-intensity data, resulting in what we call physical scale keypoints. We first produce an image mesh by backprojecting associated 2D intensity images onto the 3D range data. We detect and describe keypoints on the image mesh using an analogue of the SIFT algorithm for images with two key modifications: the process is made insensitive to viewpoint and structural discontinuities using a novel bilinear filter, and a physical scale space is constructed that exploits the reliable range measurements. Keypoints are matched between scans only when their physical scales agree, avoiding many potential false matches. Finally, the matches are rank-ordered using a new quality measure and supplied to a registration algorithm that refines each match into a rigid transformation for the entire scan pair. We report experimental results on keypoint detection and matching and range scan registration and verification in a set of difficult real-world scan pairs, showing that the new physical scale keypoints are demonstrably better than a competing approach based on backprojected SIFT keypoints.