Multiscale 3D feature extraction and matching with an application to 3D face recognition
| Autor: | Robert M. Haralick, Hadi Fadaifard, George Wolberg |
|---|---|
| Rok vydání: | 2013 |
| Předmět: |
Matching (graph theory)
Scale (ratio) Orientation (computer vision) business.industry Feature extraction ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Pattern recognition Curvature Computer Graphics and Computer-Aided Design Facial recognition system Modeling and Simulation Geometry and Topology Artificial intelligence Representation (mathematics) business Scale parameter Software ComputingMethodologies_COMPUTERGRAPHICS Mathematics |
| Zdroj: | Graphical Models. 75:157-176 |
| ISSN: | 1524-0703 |
| DOI: | 10.1016/j.gmod.2013.01.002 |
| Popis: | We present a new multiscale surface representation for 3D shape matching that is based on scale-space theory. The representation, Curvature Scale-Space 3D (CS3), is well-suited for measuring dissimilarity between (partial) surfaces having unknown position, orientation, and scale. The CS3 representation is obtained by evolving the surface curvatures according to the heat equation. This evolution process yields a stack of increasingly smoothed surface curvatures that is useful for keypoint extraction and descriptor computations. We augment this information with an associated scale parameter at each stack level to define our multiscale CS3 surface representation. The scale parameter is necessary for automatic scale selection, which has proven to be successful in 2D scale-invariant shape matching applications. We show that our keypoint and descriptor computation approach outperforms many of the leading methods. The main advantages of our representation are its computational efficiency, lower memory requirements, and ease of implementation. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
Full Text from ScienceDirect