Fast asymmetric learning for cascade face detection

IEEE Transactions on Pattern Analysis and Machine Intelligence
Jianxin WuJames M Rehg

Abstract

A cascade face detector uses a sequence of node classifiers to distinguish faces from non-faces. This paper presents a new approach to design node classifiers in the cascade detector. Previous methods used machine learning algorithms that simultaneously select features and form ensemble classifiers. We argue that if these two parts are decoupled, we have the freedom to design a classifier that explicitly addresses the difficulties caused by the asymmetric learning goal. There are three contributions in this paper. The first is a categorization of asymmetries in the learning goal, and why they make face detection hard. The second is the Forward Feature Selection (FFS) algorithm and a fast pre- omputing strategy for AdaBoost. FFS and the fast AdaBoost can reduce the training time by approximately 100 and 50 times, in comparison to a naive implementation of the AdaBoost feature selection method. The last contribution is Linear Asymmetric Classifier (LAC), a classifier that explicitly handles the asymmetric learning goal as a well-defined constrained optimization problem. We demonstrated experimentally that LAC results in improved ensemble classifier performance.

References

Sep 22, 1999·Neural Computation·Y Amit, D Geman

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Citations

Mar 17, 2010·The International Journal of Cardiovascular Imaging·Uday KurkureIoannis A Kakadiaris
Sep 5, 2013·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society·Fanglin ChenJie Zhou
Jun 26, 2013·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society·Jianxin WuJames M Rehg
Sep 10, 2015·IEEE Transactions on Pattern Analysis and Machine Intelligence·Tianfu Wu, Song-Chun Zhu
Sep 18, 2010·IEEE Transactions on Pattern Analysis and Machine Intelligence·Liya Ding, Aleix M Martinez
Jan 4, 2012·IEEE Transactions on Pattern Analysis and Machine Intelligence·Mohammad Javad Saberian, Nuno Vasconcelos
Dec 20, 2008·IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics : a Publication of the IEEE Systems, Man, and Cybernetics Society·Xu-Ying LiuZhi-Hua Zhou
Jan 1, 2012·IEEE Transactions on Neural Networks and Learning Systems·Peng WangHong Zheng
Jun 24, 2010·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society·Sakrapee PaisitkriangkraiJian Zhang
Jul 6, 2010·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society·Chunhua ShenJian Zhang
Sep 4, 2015·IEEE Transactions on Pattern Analysis and Machine Intelligence·Sakrapee PaisitkriangkraiAnton van den Hengel
Feb 22, 2017·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society·Mohammad SabokrouReinhard Klette
Jul 2, 2019·Medical Image Analysis·Yunxiang MaoZhaozheng Yin

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