Deformable Parts Model for People Detection in Heavy Machines Applications

被引：0

作者：

Bui, Manh-Tuan ^{[1
]}

Fremont, Vincent ^{[1
]}

Boukerroui, Djamal ^{[1
]}

Letort, Pierrick ^{[2
]}

机构：

[1] UTC, CNRS Heudiasyc UMR 7253, Compiegne, France

[2] Tech Ctr Mech Ind CETIM, Senlis, France

来源：

2014 13TH INTERNATIONAL CONFERENCE ON CONTROL AUTOMATION ROBOTICS & VISION (ICARCV) | 2014年

关键词：

Heavy machines; pedestrian detection; deformable part model; fisheye images; histogram of oriented gradients; latent support vector machine;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper we focus on the evaluation of the deformable part model (DPM) proposed by Felzenszwalb et al. [10] in the context of vision-based people detection in heavy machines applications. The proposed system uses a single fisheye camera to provide a wide field-of-view (FOV) at low cost. However, the fisheye optical distortions present several difficulties for image processing and object recognition. The DPM approach shows important flexibility when dealing with varying object's form. It gives good performances on people detection when images present strong fisheye distortions. Base on the analysis of DPM in the context of fisheye image, we proposed an adaptive detector which is more suitable.

引用

页码：389 / 394

页数：6

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