DocumentCode
3019929
Title
A robustness and real-time face detection algorithm in complex background
Author
Lang, Li-ying ; Gu, Wei-wei
Author_Institution
Hebei Univ. of Eng., Handan, China
fYear
2009
fDate
12-15 July 2009
Firstpage
22
Lastpage
25
Abstract
Because AdaBoost cascade face detection algorithm has a very outstanding performance, AdaBoost face detection is the mainstream algorithm currently. But it can produce misjudgment at a similar facial feature regional, particularly in the detection of more complicated image background circumstances misjudgment is even more serious. In view of reasons above, in this paper, a new algorithm was proposed and named A-SCS algorithm, which is increased skin color segmentation after detected face region use the AdaBoost algorithm. This algorithm makes full use of the image useful information, and greatly reduced the possibility of misjudgment. Compare to AdaBoost algorithm and skin color segmentation algorithm, the algorithm mentioned in this paper reduced the false detecting rate in complex background image, At the same time, it is of definite robustness. Simulated experimental results by Matlab indicate that this algorithm is faster and accuracy. Therefore it can be applied to real-time face detection system.
Keywords
image colour analysis; image segmentation; matrix algebra; object detection; A-SCS algorithm; AdaBoost cascade face detection algorithm; Matlab; complex background image; false detecting rate; self-adaptation boosting algorithm; skin color segmentation algorithm; Algorithm design and analysis; Colored noise; Face detection; Image segmentation; Mathematical model; Pattern analysis; Pattern recognition; Robustness; Skin; Wavelet analysis; AdaBoost; Color space; Skin color model; Skin color segmentation; face detection;
fLanguage
English
Publisher
ieee
Conference_Titel
Wavelet Analysis and Pattern Recognition, 2009. ICWAPR 2009. International Conference on
Conference_Location
Baoding
Print_ISBN
978-1-4244-3728-3
Electronic_ISBN
978-1-4244-3729-0
Type
conf
DOI
10.1109/ICWAPR.2009.5207441
Filename
5207441
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