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一种新的Adaboost快速训练算法
引用本文:王海川,张立明.一种新的Adaboost快速训练算法[J].复旦学报(自然科学版),2004,43(1):27-33.
作者姓名:王海川  张立明
作者单位:复旦大学,电子工程系,上海,200433
基金项目:国家自然科学基金资助项目(60171037)
摘    要:提出了一种新的Adaboost快速训练方法,解决了基于Adaboost的人脸检测算法中结构复杂、训练非常耗时的问题.新方法从两方面提高训练速度:直接求解训练中Adaboost目标函数;在直接求解算法基础上,使用了双阈值简单分类器构造强分类器的Adaboost检测器结构。

关 键 词:模式识别  Adaboost算法  人脸检测  机器学习
文章编号:0427-7104(2004)01-0027-07

A Novel Fast Training Algorithm for Adaboost
WANG Hai-chuan,ZHANG Li-ming.A Novel Fast Training Algorithm for Adaboost[J].Journal of Fudan University(Natural Science),2004,43(1):27-33.
Authors:WANG Hai-chuan  ZHANG Li-ming
Abstract:Recently the human face detection system based on Adaboost is successfully used in application areas because of its high speed and accepted detection rates, but building this system is very complex and its training time is extremely long. Numerous weaker classifiers need to be updated in the Adaboost during the training stage. A new fast training algorithm for Adaboost is proposed to solve this problem. Two methods are adopted to accelerate the training:(1) A method to directly solve the parameters of single weaker classifier is proposed, making the training speed is higher than probability method about 20 times and higher than artificial neural network thousands of times; (2) A double threshold decision for single weaker classifier is introduced, and the number of weaker classifiers in the Adaboost system is reduced, which simplifies the structure of the detection system. Based on the simplified detector, both the training time and the detecting time can be reduced.
Keywords:pattern recognition  Adaboost  face detection  machine learning
本文献已被 CNKI 维普 万方数据 等数据库收录!
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