PI Diagram Based Face Detection with AdaBoost in Color Image

被引:0
作者
Gao, ZhiSheng [1 ]
Xie, ChunZhi [1 ]
机构
[1] Xihua Univ, Sch Math & Comp Engn, Chengdu, Peoples R China
来源
2009 INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND COMPUTATIONAL INTELLIGENCE, VOL II, PROCEEDINGS | 2009年
关键词
PCA; PI Diagram; Face Detection; Adaboost;
D O I
10.1109/AICI.2009.261
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper proposes a novel method for detecting faces in color images using Ada Boost algorithm combined with PI diagram. First, potential face area is detected using PI diagram which is constructed by the principal vector of image's RGB vectors and illumination intensity. Then, the full areas are gotten by the growth algorithm. Finally, these face candidates are scanned by the cascade classifier based on Ada Boost for more accurate face detection. Experiments show that our approach is accurate than Ada Boost and has lower error detected rate than Skin color method.
引用
收藏
页码:432 / 435
页数:4
相关论文
共 50 条
[21]   Efficient Improvement for Adaboost Based Face Detection System [J].
Wu, PuFeng ;
Liu, Hongzhi ;
Cao, Xixin ;
Liu, Jing ;
Wu, Zhonghai .
11TH INTERNATIONAL CONFERENCE ON ADVANCED COMMUNICATION TECHNOLOGY, VOLS I-III, PROCEEDINGS,: UBIQUITOUS ICT CONVERGENCE MAKES LIFE BETTER!, 2009, :1453-+
[22]   A novel face detection algorithm based on PCA and Adaboost [J].
Shuang, Liu .
2014 SIXTH INTERNATIONAL CONFERENCE ON MEASURING TECHNOLOGY AND MECHATRONICS AUTOMATION (ICMTMA), 2014, :38-41
[23]   An SVM-AdaBoost-based face detection system [J].
Owusu, Ebenezer ;
Zhan, Yong-Zhao ;
Mao, Qi-Rong .
JOURNAL OF EXPERIMENTAL & THEORETICAL ARTIFICIAL INTELLIGENCE, 2014, 26 (04) :477-491
[24]   AdaBoost-based face detection for embedded systems [J].
Yang, Ming ;
Crenshaw, James ;
Augustine, Bruce ;
Mareachen, Russell ;
Wu, Ying .
COMPUTER VISION AND IMAGE UNDERSTANDING, 2010, 114 (11) :1116-1125
[25]   Adaboost Face Detection Based on Improved Covariance Feature [J].
Li, Rui ;
Li, Changfeng .
JOURNAL OF COMPUTERS, 2014, 9 (05) :1077-1082
[26]   FaceDCAPTCHA: Face detection based color image CAPTCHA [J].
Goswami, Gaurav ;
Powell, Brian M. ;
Vatsa, Mayank ;
Singh, Richa ;
Noore, Afzel .
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, 2014, 31 :59-68
[27]   Face Detection Technology Based on Combining Skin Color Model with Improved Adaboost Algorithm [J].
Li, Zhi-Zhen ;
Zeng, Qing-Hua ;
Li, Xiang-Dong ;
Yang-Yu .
2019 IEEE 4TH INTERNATIONAL CONFERENCE ON SIGNAL AND IMAGE PROCESSING (ICSIP 2019), 2019, :381-384
[28]   A New Approach to Face Detection based on YCgCr Color Model and Improved AdaBoost Algorithm [J].
Mohanty, Rosali ;
Raghunadh, M. V. .
2016 INTERNATIONAL CONFERENCE ON COMMUNICATION AND SIGNAL PROCESSING (ICCSP), VOL. 1, 2016, :1392-1396
[29]   Face detection in complex background based on Adaboost algorithm and YCbCr skin color model [J].
Ge, Wei ;
Han, Chunling ;
Quan, Wei .
MIPPR 2015: PATTERN RECOGNITION AND COMPUTER VISION, 2015, 9813
[30]   Face Detection based on Improved Neural Network and Adaboost Algorithm [J].
Wang, Ziyang .
2017 INTERNATIONAL CONFERENCE ON SMART GRID AND ELECTRICAL AUTOMATION (ICSGEA), 2017, :235-238