A 3D Face Recognition Algorithm Using Histogram-based Features (English)

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We present an automatic face recognition approach, which relies on the analysis of the three-dimensional facial surface. The proposed approach consists of two basic steps, namely a precise fully automatic normalization stage followed by a histogram-based feature extraction algorithm. During normalization the tip and the root of the nose are detected and the symmetry axis of the face is determined using a PCA analysis and curvature calculations. Subsequently, the face is realigned in a coordinate system derived from the nose tip and the symmetry axis, resulting in a normalized 3D model. The actual region of the face to be analyzed is determined using a simple statistical method. This area is split into disjoint horizontal subareas and the distribution of depth values in each subarea is exploited to characterize the face surface of an individual. Our analysis of the depth value distribution is based on a straightforward histogram analysis of each subarea. When comparing the feature vectors resulting from the histogram analysis we apply three different similarity metrics. The proposed algorithm has been tested with the FRGC v2 database, which consists of 4950 range images. Our results indicate that the city block metric provides the best classification results with our feature vectors. The recognition system achieved an equal error rate of 5.89% with correctly normalized face models.

  • Title:
    A 3D Face Recognition Algorithm Using Histogram-based Features
  • Author / Creator:
  • Published in:
  • Publisher:
    The Eurographics Association
  • Place of publication:
    Postfach 8043, 38621 Goslar, Germany
  • Year of publication:
    2008
  • Size:
    7 pages
  • ISBN:
  • ISSN:
  • DOI:
  • Type of media:
    Conference paper
  • Type of material:
    Electronic Resource
  • Language:
    English
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Table of contents conference proceedings

The tables of contents are generated automatically and are based on the data records of the individual contributions available in the index of the TIB portal. The display of the Tables of Contents may therefore be incomplete.

1
Characterizing Shape Using Conformal Factors
Ben-Chen, Mirela / Gotsman, Craig | 2008
9
3D Object Retrieval using an Efficient and Compact Hybrid Shape Descriptor
Papadakis, Panagiotis / Pratikakis, Ioannis / Theoharis, Theoharis / Passalis, Georgios / Perantonis, Stavros | 2008
17
Isometry-invariant Matching of Point Set Surfaces
Ruggeri, Mauro R. / Saupe, Dietmar | 2008
25
Markov Random Fields for Improving 3D Mesh Analysis and Segmentation
Lavoué, Guillaume / Wolf, Christian | 2008
33
Part Analogies in Sets of Objects
Shalom, Shy / Shapira, Lior / Shamir, Ariel / Cohen-Or, Daniel | 2008
41
Similarity Score Fusion by Ranking Risk Minimization for 3D Object Retrieval
Akgül, Ceyhun Burak / Sankur, Bülent / Yemez, Yücel / Schmitt, Francis | 2008
49
A Neurofuzzy Approach to Active Learning based Annotation Propagation for 3D Object Databases
Lazaridis, Michalis / Daras, Petros | 2008
57
Face Recognition by SVMs Classification and Manifold Learning of 2D and 3D Radial Geodesic Distances
Berretti, Stefano / Bimbo, Alberto Del / Pala, Pietro / Mata, Francisco Josè Silva | 2008
65
A 3D Face Recognition Algorithm Using Histogram-based Features
Zhou, Xuebing / Seibert, Helmut / Busch, Christoph / Funk, Wolfgang | 2008
73
On-line and Open Platform for 3D Object Retrieval
Bonhomme, Benoit Le / Mustafa, B. / Celakovsky, Sasko / Preda, Marius / Preteux, Francoise / Davcev, D. | 2008
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