Pedestrian detection for UAVs using cascade classifiers with Meanshift

被引：51

作者：

Aguilar, Wilbert G. ^{[1
,2
,4
]}

Luna, Marco A. ^{[3
]}

Moya, Julio F. ^{[3
]}

Abad, Vanessa ^{[5
]}

Parra, Humberto ^{[2
]}

Ruiz, Hugo ^{[2
]}

机构：

[1] Univ Fuerzas Armadas ESPE, Ctr Invest CICTE, Sangolqui, Ecuador

[2] Univ Fuerzas Armadas ESPE, Dept Seguridad & Def, Sangolqui, Ecuador

[3] Univ Fuerzas Armadas ESPE, Dept Elect & Elect, Sangolqui, Ecuador

[4] Univ Politecn Cataluna, Res Grp GREC, Barcelona, Spain

[5] Univ Barcelona, Dept Genet, Barcelona, Spain

来源：

2017 11TH IEEE INTERNATIONAL CONFERENCE ON SEMANTIC COMPUTING (ICSC) | 2017年

关键词：

HAAR; LBP; HOG; MeanShift; People Detection; Cascade Classifiers;

D O I：

10.1109/ICSC.2017.83

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper, we propose an algorithm for pedestrian detection focusing on UAV applications. Our proposal is based on a combination of Haar-LBP features with Adaboost for the training process, and Meanshift for improving the performance of the pedestrian detector. We mount a dataset with images captured from surveillance cameras. Our dataset and algorithm are evaluated and compared with other approaches from the literature.

引用

页码：509 / 514

页数：6

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