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https://doi.org/10.1109/ccece....
Article . 2008 . Peer-reviewed
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Markerless human tracking for industrial environments

Authors: Mohanad Elshafie; Gary M. Bone;

Markerless human tracking for industrial environments

Abstract

A markerless multiple-camera vision-based 3D human tracking method for industrial environments is presented. The method can track humans in the vicinity of moving robots without using skin color cues or articulated human models. It is robust to self-occlusions and to partial occlusions caused by the robot. Foreground pixels corresponding to humans are found by background subtraction. A convex polyhedron enclosing the human(s) is generated online by bounding the foreground pixels in 3D space. Experimental results are included for a single person and multiple persons walking near a moving PUMA robot in a cluttered environment. Reliable tracking at 11.4 Hz is demonstrated using four cameras and a Pentium 4 PC. The tracking data may be used for online robot collision avoidance.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
3
Average
Average
Average