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Adaboost multi-view face detection based on YCgCr skin color model
Lan, Qi1,2; Xu, Zhiyong2
2016
Source PublicationProceedings of SPIE: 8th International Symposium on Advanced Optical Manufacturing and Testing Technology: Optical Test, Measurement Technology, and Equipment
ISSN0277-786X
Volume9684Pages:96842D
SubtypeC
AbstractTraditional Adaboost face detection algorithm uses Haar-like features training face classifiers, whose detection error rate is low in the face region. While under the complex background, the classifiers will make wrong detection easily to the background regions with the similar faces gray level distribution, which leads to the error detection rate of traditional Adaboost algorithm is high. As one of the most important features of a face, skin in YCgCr color space has good clustering. We can fast exclude the non-face areas through the skin color model. Therefore, combining with the advantages of the Adaboost algorithm and skin color detection algorithm, this paper proposes Adaboost face detection algorithm method that bases on YCgCr skin color model. Experiments show that, compared with traditional algorithm, the method we proposed has improved significantly in the detection accuracy and errors. © 2016 SPIE.
KeywordAdaptive Boosting Color Color Codes Color Image Processing Error Detection Errors Feature Extraction Manufacture Optical Testing Signal Detection
DOI10.1117/12.2243232
Indexed BySCI ; Ei
Language英语
Funding OrganizationChinese Academy of Sciences, Institute of Optics and Electronics (IOE) ; The Chinese Optical Society (COS)
WOS IDWOS:000387429500085
Citation statistics
Cited Times:1[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ioe.ac.cn/handle/181551/8514
Collection光电探测与信号处理研究室(五室)
Affiliation1. Institute of Optics and Electronics, Chinese Academy of Science, Sichuan Province
2.610209, China
3. University of Chinese Academy of Sciences, Beijing
4.100039, China
Recommended Citation
GB/T 7714
Lan, Qi,Xu, Zhiyong. Adaboost multi-view face detection based on YCgCr skin color model[J]. Proceedings of SPIE: 8th International Symposium on Advanced Optical Manufacturing and Testing Technology: Optical Test, Measurement Technology, and Equipment,2016,9684:96842D.
APA Lan, Qi,&Xu, Zhiyong.(2016).Adaboost multi-view face detection based on YCgCr skin color model.Proceedings of SPIE: 8th International Symposium on Advanced Optical Manufacturing and Testing Technology: Optical Test, Measurement Technology, and Equipment,9684,96842D.
MLA Lan, Qi,et al."Adaboost multi-view face detection based on YCgCr skin color model".Proceedings of SPIE: 8th International Symposium on Advanced Optical Manufacturing and Testing Technology: Optical Test, Measurement Technology, and Equipment 9684(2016):96842D.
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