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Author:

Jiang, Bin (Jiang, Bin.) | Jia, Ke-Bin (Jia, Ke-Bin.) (Scholars:贾克斌) | Wu, Qiang (Wu, Qiang.)

Indexed by:

EI Scopus

Abstract:

Facial Expression Recognition has become a hot research direction in human computer interaction, machine learning and image processing. However, the inaccuracy of facial expression similarity measure is always a key problem in facial expression classification. In order to solve this problem, a novel algorithm which is based on Discriminative Component Analysis algorithm, is proposed in this paper. Compared with Discriminative Component Analysis, our algorithm is based on maximizing within-class distance and minimizing between-class distance to choose chunklets, which guarantee the stability and accuracy of algorithm. The mean recognition rates are 80.42% and 95.71% under the condition of using hold-out method and leave-one-out method respectively. Experimental results show the effectiveness of our algorithm. © 2012 IEEE.

Keyword:

Human computer interaction Face recognition Multimedia signal processing

Author Community:

  • [ 1 ] [Jiang, Bin]College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing, China
  • [ 2 ] [Jia, Ke-Bin]College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing, China
  • [ 3 ] [Wu, Qiang]College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing, China

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Source :

Year: 2012

Page: 399-402

Language: English

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count: 1

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 5

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