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Author:

Deng, Wanghua (Deng, Wanghua.) | Liang, Xun (Liang, Xun.)

Indexed by:

EI Scopus

Abstract:

Face detection is a branch field originated from face recognition. In recent years, face detection has shown important significance and value in daily produce and application. A face detection method based on BP neural network and improved AdaBoost algorithm is proposed in this paper. First, Using BP neural network instead of YCbCr gaussian model to build skin color model. Meanwhile, a new method of weight updating for AdaBoost algorithm is proposed. The distance between the threshold and the sample is introduced into the update of weight. Besides the weight has a boundary value. Finally, BP neural network is used to obtain the skin color candidate areas in the image, and the improved AdaBoost algorithm is used to accurately detect the face in the image. Based on our experimental result, the new solution using our BP neural network and improved AdaBoost algorithm performs higher accuracy than the existing approach. © 2018 IEEE.

Keyword:

Gaussian distribution Image enhancement Face recognition Chromium compounds Cloud computing Backpropagation Adaptive boosting Neural networks

Author Community:

  • [ 1 ] [Deng, Wanghua]Beijing University of Technology, Beijing; 100124, China
  • [ 2 ] [Liang, Xun]Beijing University of Technology, Beijing; 100124, China

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Source :

Year: 2019

Page: 395-399

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: 13

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