3D face recognition based on g-h shape variation

  • Authors:
  • Chenghua Xu;Yunhong Wang;Tieniu Tan;Long Quan

  • Affiliations:
  • National Laboratory of Pattern Recognition, Institute of Automation, CAS, Beijing, P R China;National Laboratory of Pattern Recognition, Institute of Automation, CAS, Beijing, P R China;National Laboratory of Pattern Recognition, Institute of Automation, CAS, Beijing, P R China;Department of Computer Science, Hong Kong University of Science and Technology, Kowloon, Hong Kong

  • Venue:
  • SINOBIOMETRICS'04 Proceedings of the 5th Chinese conference on Advances in Biometric Person Authentication
  • Year:
  • 2004

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Abstract

Face recognition has been an interesting issue in pattern recognition over the past few decades In this paper, we propose a new method for face recognition using 3D information During preprocessing, the scanned 3D point clouds are first registered together, and at the same time, the regular meshes are generated Then the novel shape variation representation based on Gaussian-Hermite moments (GH-SVI) is proposed to characterize an individual Experimental results on the 3D face database 3DPEF, with complex pose and expression variations, and 3D_RMA, likely the largest 3D face database currently available, demonstrate that the proposed features are very important to characterize an individual.