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.File in questo prodotto:
File | Dimensione | Formato | |
---|---|---|---|
ICINCO2014-reprint.pdf
Accesso riservato
:
Post-Print (DRAFT o Author’s Accepted Manuscript-AAM)
Dimensione
1.2 MB
Formato
Adobe PDF
|
1.2 MB | Adobe PDF | Visualizza/Apri |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.