oru.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Estimating the 3d position of humans wearing a reflective vest using a single camera system
Örebro University, School of Science and Technology. (MRO)
Örebro University, School of Science and Technology. (MRO)ORCID iD: 0000-0002-2953-1564
2012 (English)In: Proceedings of the International Conference on Field and Service Robotics (FSR), Springer, 2012Conference paper, Published paper (Refereed)
Abstract [en]

This paper presents a novel possible solution for people detection and estimation of their 3D position in challenging shared environments. Addressing safety critical applications in industrial environments, we make the basic assumption that people wear reflective vests. In order to detect these vests and to discriminate them from other reflective material, we propose an approach based on a single camera equipped with an IR flash. The camera acquires pairs of images, one with and one without IR flash, in short succession. The images forming a pair are then related to each other through feature tracking, which allows to discard features for which the relative intensity difference is small and which are thus not believed to belong to a reflective vest. Next, the local neighbourhood of the remaining features is further analysed. First, a Random Forest classifier is used to discriminate between features caused by a reflective vest and features caused by some other reflective materials. Second, the distance between the camera and the vest features is estimated using a Random Forest regressor. The proposed system was evaluated in one indoor and two challenging outdoor scenarios. Our results indicate very good classification performance and remarkably accurate distance estimation especially in combination with the SURF descriptor, even under direct exposure to sunlight.

Place, publisher, year, edition, pages
Springer, 2012.
Series
Springer Tracts in Advanced Robotics, ISSN 1610-7438
National Category
Computer Sciences
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:oru:diva-28889OAI: oai:DiVA.org:oru-28889DiVA, id: diva2:619101
Conference
2012 International Conference on Field and Service Robotics (FSR)
Projects
People Detection, Industrial Safety, Reflective Vest DetectionAvailable from: 2013-05-02 Created: 2013-05-02 Last updated: 2018-01-11Bibliographically approved

Open Access in DiVA

No full text in DiVA

Authority records BETA

Mosberger, RafaelAndreasson, Henrik

Search in DiVA

By author/editor
Mosberger, RafaelAndreasson, Henrik
By organisation
School of Science and Technology
Computer Sciences

Search outside of DiVA

GoogleGoogle Scholar

urn-nbn

Altmetric score

urn-nbn
Total: 349 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf