In an industrial scenario the capability to detect and track human workers entering a robotic cell represents a fundamental requirement to enable safe and efficient human-robot cooperation. This paper proposes a new approach to the problem of Human Detection and Tracking based on low-cost commercial RGB surveillance cameras, image warping techniques, computer vision algorithms, efficient data structures such as k-dimensional trees and particle filtering. Results of several validation experiments are presented.

Multiple Camera Human Detection and Tracking inside a Robotic Cell - An Approach based on Image Warping, Computer Vision, K-d Trees and Particle Filtering

RAGAGLIA, MATTEO;BASCETTA, LUCA;ROCCO, PAOLO
2014-01-01

Abstract

In an industrial scenario the capability to detect and track human workers entering a robotic cell represents a fundamental requirement to enable safe and efficient human-robot cooperation. This paper proposes a new approach to the problem of Human Detection and Tracking based on low-cost commercial RGB surveillance cameras, image warping techniques, computer vision algorithms, efficient data structures such as k-dimensional trees and particle filtering. Results of several validation experiments are presented.
2014
Proceedings of the 11th International Conference On Informatics in Control, Automation and Robotics ICINCO 2014
9781479979202
AUT
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/821934
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