Authors:
Matteo Ragaglia
;
Luca Bascetta
and
Paolo Rocco
Affiliation:
Politecnico di Milano, Italy
Keyword(s):
Human Detection and Tracking, Robotic Cell Supervision, Computer Vision, Image Warping, Background/Foreground Segmentation, K-d Tree, Particle Filtering.
Related
Ontology
Subjects/Areas/Topics:
Control and Supervision Systems
;
Engineering Applications
;
Image Processing
;
Informatics in Control, Automation and Robotics
;
Intelligent Control Systems and Optimization
;
Perception and Awareness
;
Robotics and Automation
;
Signal Processing, Sensors, Systems Modeling and Control
;
Vision, Recognition and Reconstruction
Abstract:
In an industiral 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 kdimensional trees and particle filtering. Results of several validation experiments are presented.