[1]李梦涵,熊淑华,熊文,等. 多尺度级联行人检测算法的研究与实现[J].计算机技术与发展,2014,24(08):10-13.
　LI Meng-han,XIONG Shu-hua,XIONG Wen,et al. Research and Realization of Pedestrian Detection Algorithm by Multi-scale Cascaded Features[J].,2014,24(08):10-13.
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 多尺度级联行人检测算法的研究与实现(/HTML)
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
24
期数:
2014年08期
页码:
10-13
栏目:
智能、算法、系统工程
出版日期:
2014-08-10

文章信息/Info

Title:
 Research and Realization of Pedestrian Detection Algorithm by Multi-scale Cascaded Features
文章编号:
1673-629X（2014）08-0010-04
作者:
 李梦涵; 熊淑华; 熊文; 魏育才; 李杨
 四川大学 电子信息学院
Author(s):
 LI Meng-han；XIONG Shu-hua；XIONG Wen；WEI Yu-cai；LI Yang
关键词:
 ; 行人检测; 方向梯度直方图; 多尺度; 级联Adaboost
Keywords:
 ; pedestrian detection; HOG; multi-scale; cascaded Adaboost
分类号:
TP301.6
文献标志码:
A
Abstract:
 Pedestrian detection algorithm is a method to decide whether there exists pedestrian or not in the picture by characters of pedes-trians combined with classifiers. In this paper,an improved pedestrian detection algorithm is advanced based on the traditional HOG meth-od and Adaboost classifying idea. In this algorithm,use the multi-scale HOG features to extract the features in the detection region,then the cascaded Adaboost classifiers with multi-scale features are used to judge,getting its result input into the next level of classifier,and fi-nally achieve the goal of pedestrian detection. The experimental result shows that the cascaded classifiers using multi-scale features per-forms better in pedestrian detection,which achieves higher detection precision at little cost of computing time.

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更新日期/Last Update: 2015-03-17