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Sensors 2016, 16(1), 128;

Vision-Based People Detection System for Heavy Machine Applications

Sorbonne Universités, Université de Technologie de Compiègne, CNRS, UMR 7253, Heudiasyc-CS 60 319, 60 203 Compiègne Cedex, France
Technical Center for the Mechanical Industry (CETIM), 60300 Senlis, France
Author to whom correspondence should be addressed.
Academic Editor: Vittorio M. N. Passaro
Received: 12 October 2015 / Revised: 10 January 2016 / Accepted: 13 January 2016 / Published: 20 January 2016
(This article belongs to the Section Physical Sensors)
Full-Text   |   PDF [13314 KB, uploaded 20 January 2016]   |  


This paper presents a vision-based people detection system for improving safety in heavy machines. We propose a perception system composed of a monocular fisheye camera and a LiDAR. Fisheye cameras have the advantage of a wide field-of-view, but the strong distortions that they create must be handled at the detection stage. Since people detection in fisheye images has not been well studied, we focus on investigating and quantifying the impact that strong radial distortions have on the appearance of people, and we propose approaches for handling this specificity, adapted from state-of-the-art people detection approaches. These adaptive approaches nevertheless have the drawback of high computational cost and complexity. Consequently, we also present a framework for harnessing the LiDAR modality in order to enhance the detection algorithm for different camera positions. A sequential LiDAR-based fusion architecture is used, which addresses directly the problem of reducing false detections and computational cost in an exclusively vision-based system. A heavy machine dataset was built, and different experiments were carried out to evaluate the performance of the system. The results are promising, in terms of both processing speed and performance. View Full-Text
Keywords: heavy machines; sensor fusion; pedestrian detection; deformable part model; fisheye images; histogram of oriented gradients heavy machines; sensor fusion; pedestrian detection; deformable part model; fisheye images; histogram of oriented gradients

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Fremont, V.; Bui, M.T.; Boukerroui, D.; Letort, P. Vision-Based People Detection System for Heavy Machine Applications. Sensors 2016, 16, 128.

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