A method of face detection under complicated background

ZHANG Yun-long; XIE Ze-qi; ZHANG Hui-min; DONG Cheng-ting

doi:10.13873/j.1000-97872011.06.028

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A method of face detection under complicated background

更新时间：2025-09-11

- A method of face detection under complicated background
- Vol. 30, Issue 6, Pages: 42-44+48(2011)
- 作者机构：
  
  郑州大学西亚斯国际学院
- 作者简介：
- 基金信息：
- DOI：10.13873/j.1000-97872011.06.028
  CLC： TP391.41
- Published：2011
- 稿件说明：
移动端阅览
[1]张云龙,谢泽奇,张会敏,董承廷.一种复杂背景下的人脸检测方法[J].传感器与微系统,2011,30(06):42-44+48.

ZHANG Yun-long, XIE Ze-qi, ZHANG Hui-min, et al. A method of face detection under complicated background[J]. 2011, 30(6): 42-44+48.
[1]张云龙,谢泽奇,张会敏,董承廷.一种复杂背景下的人脸检测方法[J].传感器与微系统,2011,30(06):42-44+48. DOI： 10.13873/j.1000-97872011.06.028.

ZHANG Yun-long, XIE Ze-qi, ZHANG Hui-min, et al. A method of face detection under complicated background[J]. 2011, 30(6): 42-44+48. DOI： 10.13873/j.1000-97872011.06.028.

摘要

针对在复杂背景下现有人脸检测算法存在检测率低和误检率高等问题

提出了一种基于改进AdaBoost算法和肤色校验相结合的彩色图像人脸检测方法。首先对传统AdaBoost算法进行了改进

通过改进样本权值参数和弱分类器加权参数

有效地抑制了困难样本权值的过分增大

加强了分类器对样本的识别能力

并提高了系统的检测率;然后将AdaBoost算法检测结果用YCbCr空间的肤色模型进行筛选

过滤误检的非人脸区域

进一步降低误检率。实验结果表明:该方法在复杂背景下极大地保证改进AdaBoost算法的人脸检测速度和准确性的同时

降低了误检率

具有较好的鲁棒性。

Abstract

Aiming at resolving the problems of face detection algorithm under complicated background such as low detection rate and high false-alarm-rate etc

an effective method of face detection in color images based on improved AdaBoost algorithm and skin color is presented.By improving parameters of sample weights and weak classifier weighting value

the traditional AdaBoost algorithm has been improved.It effectively restrains the excessive increase of weights of hard samples

strengthens the capacity of classifier for recognition of samples and the system detection rate is increased.The detection result is screened with YCbCr space skin color model to filter error-detected "non-face" area.The experimental results indicate that this method assures the face detection speed and precision of improved AdaBoost algorithm under complicated background

decreases the false-alarm-rate and has strong robustness.

关键词

Keywords

references

基于肤色分割和改进Gabor滤波相结合的人脸检测 [J]. 张国伟,于金霞,陈现查. 计算机测量与控制 . 2010(01)

基于改进的AdaBoost算法的人脸检测与定位 [J]. 徐前,赵德安,赵建波. 传感器与微系统 . 2010(01)

一种改进的AdaBoost算法——AD AdaBoost [J]. 李闯,丁晓青,吴佑寿. 计算机学报 . 2007(01)

Automatic character detection and segmentation in natural scene images [J]. ZHU Kai-hua, QI Fei-hu, JIANG Ren-jie, XU Li (Department of Computer Science and Technology, Shanghai Jiao Tong University, Shanghai 200030, China). Journal of Zhejiang University Science A(Science in Engineer . 2007(01)

人脸检测研究综述 [J]. 梁路宏,艾海舟,徐光祐,张钹. 计算机学报 . 2002(05)

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