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Author:

Yin, Baocai (Yin, Baocai.) (Scholars:尹宝才) | Shi, Qin (Shi, Qin.) | Wang, Chengzhang (Wang, Chengzhang.) | Sun, Yanfeng (Sun, Yanfeng.) (Scholars:孙艳丰)

Indexed by:

EI Scopus

Abstract:

In this present study, a face recognition method is proposed based on improved adaptive principal component extraction algorithm with Morphablc model. Improved adaptive principal component extraction algorithm is proposed to compress high-dimensional facial image data. A 3D Morphable model is adopted to derive multiple images of a face from a single facial image. The experimental results on ORL and UMIST face database show the proposed method gives impressive performance and improvement compared with the conventional Eigenface methods.

Keyword:

Classification (of information) Face recognition Mathematical techniques Image reconstruction Feature extraction Principal component analysis

Author Community:

  • [ 1 ] [Yin, Baocai]Beijing Municipal Multimedia and Intelligent Software Key Lab. Science, Beijing University of Technology, Beijing 100022, China
  • [ 2 ] [Shi, Qin]Beijing Municipal Multimedia and Intelligent Software Key Lab. Science, Beijing University of Technology, Beijing 100022, China
  • [ 3 ] [Wang, Chengzhang]Beijing Municipal Multimedia and Intelligent Software Key Lab. Science, Beijing University of Technology, Beijing 100022, China
  • [ 4 ] [Sun, Yanfeng]Beijing Municipal Multimedia and Intelligent Software Key Lab. Science, Beijing University of Technology, Beijing 100022, China

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Source :

Journal of Computational Information Systems

ISSN: 1553-9105

Year: 2005

Issue: 2

Volume: 1

Page: 329-336

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 8

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