计算机技术与发展2011，Vol.21Issue(9)：99-102,106,5.
基于多尺度-多形状HOG特征的行人检测方法
Pedestrian Detection Based on Multi-Scale and Multi-Shape HOG Features
摘要
Abstract
A fast and automatic people detection method is proposed. The multi-scale and multi-shape histogram of oriented gradient (HOG) features are extracted, which serve as a powerful description of human shapes;The extracted features are then fed into a cascade of classifiers trained by Adabcost algorithm to greatly accelerate the people detection scheme. The proposed method is independent from background models as well as color information in images, which is highly unreliable due to disturbance. This method is robust agains: human posture variances, lightening fluctuations as well as background cluttering. Experimental results validate the favorable performance of high accuracy and computational efficiency of the proposed method.关键词
方向梯度直方图/行人检测/Adaboost/机器学习Key words
histogram of oriented gradient/pedestrian detection/Adaboost/machine learning分类
信息技术与安全科学引用本文复制引用
牛杰,钱堃..基于多尺度-多形状HOG特征的行人检测方法[J].计算机技术与发展,2011,21(9):99-102,106,5.基金项目
江苏省现代教育技术研究2011年度技术应用重点课题(2011-R-18926) （2011-R-18926）
