Titlebook: Human Ear Recognition by Computer; Bir Bhanu,Hui Chen Book 2008 Springer-Verlag London 2008 3D.Computer Vision.Ear Recognition.Ear-based i

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Recognizing 3D Ears Using Ear Helix/Anti-Helix,x parts, which results in the one-to-one correspondence of the ear helix and anti-helix between the reference ear shape model and the input image. We propose to match 3D ears using the ear helix/antihelix representation [1]. First the correspondence of ear helix and antihelix parts (available from t

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Recognizing 3D Ears Using Local Surface Patches,tor, is characterized by a centroid, a local surface type and a 2D histogram. The 2D histogram shows the frequency of occurrence of shape index values vs. the angles between the normal of reference feature point and that of its neighbors. The proposed human recognition system using the LSP represent

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Rapid 3D Ear Indexing and Recognition,es for correspondences, and a support vector machine (SVM)- based learning technique for ranking the hypotheses. The local surface patch (LSP) representation is used to find the correspondence between a model-test pair. Due to its high dimensionality, an embedding algorithm is used that maps the fea

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Applications of the Proposed Techniques,e patch (LSP) representation can be used to recognize 3D general objects; the global-to-local registration with the optimization framework can handle non-rigid shape registration. We discuss the applications of these two techniques in this chapter with several non-ear examples.

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2191-6586 interest to researchers, developers and decision makers who are involved in robust human recognition by computer for a large number of practical applications..978-1-84996-733-4978-1-84800-129-9Series ISSN 2191-6586 Series E-ISSN 2191-6594