Deformable Parts Model for People Detection in Heavy Machines Applications - Archive ouverte HAL
Communication Dans Un Congrès Année : 2014

Deformable Parts Model for People Detection in Heavy Machines Applications

Résumé

In this paper we focus on the evaluation of the de-formable 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.
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Dates et versions

hal-01098786 , version 1 (29-12-2014)

Identifiants

  • HAL Id : hal-01098786 , version 1

Citer

Manh-Tuan Bui, Vincent Frémont, Djamal Boukerroui, Pierrick Letort. Deformable Parts Model for People Detection in Heavy Machines Applications. 13th International Conference on Control, Automation, Robotics & Vision (ICARCV 2014), Dec 2014, Singapour, Singapore. pp.389-394. ⟨hal-01098786⟩
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