Literature DB >> 25264956

A customized vision system for tracking humans wearing reflective safety clothing from industrial vehicles and machinery.

Rafael Mosberger1, Henrik Andreasson2, Achim J Lilienthal3.   

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.

Entities:  

Mesh:

Year:  2014        PMID: 25264956      PMCID: PMC4239879          DOI: 10.3390/s141017952

Source DB:  PubMed          Journal:  Sensors (Basel)        ISSN: 1424-8220            Impact factor:   3.576


  4 in total

1.  Survey of pedestrian detection for advanced driver assistance systems.

Authors:  David Gerónimo; Antonio M López; Angel D Sappa; Thorsten Graf
Journal:  IEEE Trans Pattern Anal Mach Intell       Date:  2010-07       Impact factor: 6.226

2.  Stereo processing by semiglobal matching and mutual information.

Authors:  Heiko Hirschmüller
Journal:  IEEE Trans Pattern Anal Mach Intell       Date:  2008-02       Impact factor: 6.226

3.  Monocular pedestrian detection: survey and experiments.

Authors:  Markus Enzweiler; Dariu M Gavrila
Journal:  IEEE Trans Pattern Anal Mach Intell       Date:  2009-12       Impact factor: 6.226

4.  Pedestrian detection: an evaluation of the state of the art.

Authors:  Piotr Dollár; Christian Wojek; Bernt Schiele; Pietro Perona
Journal:  IEEE Trans Pattern Anal Mach Intell       Date:  2012-04       Impact factor: 6.226

  4 in total

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