AUTHORS: Jakarin Smitaveja, Kingkarn Sookhanaphibarn and Chidchanok Lursinsap

ABSTRACT: Face recognition technology has been an increasingly important module in security systems. A challenging problem is how to extract features tolerant to the appearance variables such as changes in shape, illumination, and occlusion. Extracted metrical features of facial caricatures that are combined with their facial photographs in the training set are examined. The facial caricature is a personal representative amplifying perceptually significant information of individuals. Unlike Eigenfaces, Fisherfaces, and Laplacianfaces, the twenty-nine metrical features that used in this study do not depend upon illumination and occlusion variables. Our results show that facial caricature-trained neural networks outperform significantly of those

only facial photograph trained neural networks.

Keywords: Face recognition, Caricature visualization, Neural networks, Facial identification, Noise immunity

SOURCE: Smitaveja, Jakarin, Kingkarn Sookhanaphibarn, and Chidchanok Lursinsap. "Facial metrical and caricature-pattern-based learning in neural network system for face recognition." Computer and Information Science, 2009. ICIS 2009. Eighth IEEE/ACIS International Conference on. IEEE, 2009.

LINK: http://ieeexplore.ieee.org/abstract/document/5222949/

REFERENCES: 

MLA   Smitaveja, Jakarin, Kingkarn Sookhanaphibarn, and Chidchanok Lursinsap. "Facial metrical and caricature-pattern-based learning in neural network system for face recognition." 2009 Eighth IEEE/ACIS International Conference on Computer and Information Science. IEEE, 2009.
APA Smitaveja, J., Sookhanaphibarn, K., & Lursinsap, C. (2009, June). Facial metrical and caricature-pattern-based learning in neural network system for face recognition. In 2009 Eighth IEEE/ACIS International Conference on Computer and Information Science (pp. 660-665). IEEE.
ISO 690  SMITAVEJA, Jakarin; SOOKHANAPHIBARN, Kingkarn; LURSINSAP, Chidchanok. Facial metrical and caricature-pattern-based learning in neural network system for face recognition. In: 2009 Eighth IEEE/ACIS International Conference on Computer and Information Science. IEEE, 2009. p. 660-665.