Rank-Based Decision Fusion for 3D Shape-Based Face Recognition

  • Berk Gökberk
  • Albert Ali Salah
  • Lale Akarun
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3546)


In 3D face recognition systems, 3D facial shape information plays an important role. Various shape representations have been proposed in the literature. The most popular techniques are based on point clouds, surface normals, facial profiles, and statistical analysis of depth images. The contribution of the presented work can be divided into two parts: In the first part, we have developed face classifiers which use these popular techniques. A comprehensive comparison of these representation methods are given using 3D RMA dataset. Experimental results show that the linear discriminant analysis-based representation of depth images and point cloud representation perform best. In the second part of the paper, two different multiple-classifier architectures are developed to fuse individual shape-based face recognizers in parallel and hierarchical fashions at the decision level. It is shown that a significant performance improvement is possible when using rank-based decision fusion in ensemble methods.


Point Cloud Face Recognition Linear Discriminant Analysis Depth Image Gesture Recognition 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Berk Gökberk
    • 1
  • Albert Ali Salah
    • 1
  • Lale Akarun
    • 1
  1. 1.Computer Engineering DepartmentBoğaziçi UniversityTurkey

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