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Markerless human tracking for industrial environments

Mohanad Elshafie, Gary M. Bone

Year
2008
Citations
8

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.

Keywords

Computer visionArtificial intelligenceComputer sciencePixelTracking (education)Background subtractionRobot

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