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Sensors 2014, 14(10), 17952-17980; doi:10.3390/s141017952

A Customized Vision System for Tracking Humans Wearing Reflective Safety Clothing from Industrial Vehicles and Machinery

AASS Research Centre, Örebro University, 70182 Örebro, Sweden
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Received: 8 July 2014 / Revised: 5 September 2014 / Accepted: 9 September 2014 / Published: 26 September 2014
(This article belongs to the Section Physical Sensors)
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Abstract

This article presents a novel approach for vision-based detection and tracking of humans wearing high-visibility clothing with retro-reflective markers. Addressing industrial applications where heavy vehicles operate in the vicinity of humans, we deploy a customized stereo camera setup with active illumination that allows for efficient detection of the reflective patterns created by the worker’s safety garments. After segmenting reflective objects from the image background, the interest regions are described with local image feature descriptors and classified in order to discriminate safety garments from other reflective objects in the scene. In a final step, the trajectories of the detected humans are estimated in 3D space relative to the camera. We evaluate our tracking system in two industrial real-world work environments on several challenging video sequences. The experimental results indicate accurate tracking performance and good robustness towards partial occlusions, body pose variation, and a wide range of different illumination conditions. View Full-Text
Keywords: infrared vision; human detection; industrial safety, high-visibility clothing infrared vision; human detection; industrial safety, high-visibility clothing
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Mosberger, R.; Andreasson, H.; Lilienthal, A.J. A Customized Vision System for Tracking Humans Wearing Reflective Safety Clothing from Industrial Vehicles and Machinery. Sensors 2014, 14, 17952-17980.

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