Invariant surface characteristics for 3D object recognition in range images
Computer Vision, Graphics, and Image Processing - Lectures notes in computer science, Vol. 201 (G. Goos and J. Hartmanis, Eds.)
Evidence-Based Recognition of 3-D Objects
IEEE Transactions on Pattern Analysis and Machine Intelligence
Range Image Segmentation Based on Differential Geometry: A Hybrid Approach
IEEE Transactions on Pattern Analysis and Machine Intelligence
Recognizing 3-D Objects Using Surface Descriptions
IEEE Transactions on Pattern Analysis and Machine Intelligence
Representation and recognition of surface shapes in range images: a differential geometry approach
Computer Vision, Graphics, and Image Processing
Space Curve Representation and Recognition Based on Wavelet Transform Zero-Crossings
Journal of Mathematical Imaging and Vision
Hierarchical face clustering on polygonal surfaces
I3D '01 Proceedings of the 2001 symposium on Interactive 3D graphics
A survey of methods for recovering quadrics in triangle meshes
ACM Computing Surveys (CSUR)
Estimation of Error in Curvature Computation on Multi-Scale Free-Form Surfaces
International Journal of Computer Vision
A Sampling Framework for Accurate Curvature Estimation in Discrete Surfaces
IEEE Transactions on Visualization and Computer Graphics
Gauss map computation for free-form surfaces
Computer Aided Geometric Design
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In this correspondence, the application of covariance techniques to surface representation of 3-D objects is discussed and such ways of computing surface geometry are compared with traditional methods using differential geometry. It is shown how the covariance method provides surface descriptors that are invariant to rigid motions without explicitly using surface parameterizations or derivatives. Analogous covariance operators for both the Gauss and Weingarten maps are defined and a range image segmentation technique is presented that labels pixels as jump or crease discontinuities or planar, parabolic or curved region types.