Face Detection Based on Skin and Improved ICA

Yan Wang; Zheng Wu Jiang

doi:10.4028/www.scientific.net/AMR.219-220.1486

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 219-220Face Detection Based on Skin and Improved ICA

Face Detection Based on Skin and Improved ICA

Abstract:

Face detection has been developed into one independent research direction. This paper proposes a detection method based on the combination of skin color and improved ICA. The method makes face detection in color images real and abandons the conventional way of detecting grey rather than color images. Its description is as follows: In the beginning, skin color mode should be founded on the basis of a new color space called H_SI_I. Then with the help of prior knowledge, image preprocessing can be implemented to obtain candidates’ faces, which will be detected by improved ICA. Experiments demonstrate that the method proposed by this paper has better effect than the conventional face detection based on subspace as far as speed and accuracy is concerned.

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Periodical:

Advanced Materials Research (Volumes 219-220)

Pages:

1486-1490

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.219-220.1486

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Online since:

March 2011

Authors:

Yan Wang, Zheng Wu Jiang

Keywords:

Cascade, Classifier, Dual-Threshold, Face Detection, Improved ICA

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References

[1] Yang GZ, Huang TS. Human face detection in a complex background. Pattern Recognition, 1994.27(1):53-63.

DOI: 10.1016/0031-3203(94)90017-5

Google Scholar

[2] M.Nilsson, J.Nordberg, and I.Claesson: Face Detection Using Local SMQT Features and Split up SNOW Classifier, in Proc.ICASSP, (2007), p.II-589-592.

DOI: 10.1109/icassp.2007.366304

Google Scholar

[3] D.Chen, and Z.Liu: Using Color and Color Edge Histograms for SVM Based Human Face Detection, Journal of Chinese Computer Systems, vol.26, (2005)，pp.2195-2198.

Google Scholar

[4] Y.X, and X.Chen: Multiple face detection based on skin color and modified Bayes classifier Computer Engineering & Design, vol.29, (2008), pp.2304-2305.

Google Scholar

[5] X.Li, and G.Lu: Face Detection and Tracking Based on Skin Color and Facial Features, Nanjing University, (2005), pp.34-38.

Google Scholar

[6] R.zhang, G.Xue: Variants of Newton's iteration Method with Third-Order Convergence, College Mathematics, vol.21, (2005), pp.80-82.

Google Scholar

[7] H.Ai, X.Xiao, and G.Xu: Face Detection and Retrieval, Chinese Journal of Computers, vol.26, (2003), pp.877-878.

Google Scholar