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Authors: Giovanni Saggio 1 ; Francesco Cavrini 2 and Franco Di Paolo 1

Affiliations: 1 University of Rome “Tor Vergata”, Italy ; 2 Captiks S.r.l., Italy

Keyword(s): Visual Signalling, Sensory Glove, SVM.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Biomedical Engineering ; Biomedical Signal Processing ; Computational Intelligence ; Data Manipulation ; Health Engineering and Technology Applications ; Human-Computer Interaction ; Methodologies and Methods ; Neural Networks ; Neurocomputing ; Neurotechnology, Electronics and Informatics ; Pattern Recognition ; Physiological Computing Systems ; Sensor Networks ; Signal Processing ; Soft Computing ; Support Vector Machines and Applications ; Theory and Methods

Abstract: An electronic demonstrator was designed and developed to automatically interpret the signalman’s arm-and-hand visual signals. It was based on an “extended” sensory glove, which is a glove equipped with sensors to measure fingers/wrist/forearm movements, an electronic circuitry to acquire/condition/feed measured data to a personal computer, SVM based routines to classify the visual signals, and a graphical interface to represent classified data. The aim was to furnish to the Italian Aircraft Force a tool for ground-to-ground or ground-to-air communication, which can be independent from the full view of the vehicle drivers or aircraft pilots, and which can provide information redundancy to improve airport security.

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Paper citation in several formats:
Saggio, G.; Cavrini, F. and Di Paolo, F. (2015). Inedited SVM Application to Automatically Tracking and Recognizing Arm-and-Hand Visual Signals to Aircraft. In Proceedings of the 7th International Joint Conference on Computational Intelligence (ECTA 2015) - NCTA; ISBN 978-989-758-157-1, SciTePress, pages 157-162. DOI: 10.5220/0005630801570162

@conference{ncta15,
author={Giovanni Saggio. and Francesco Cavrini. and Franco {Di Paolo}.},
title={Inedited SVM Application to Automatically Tracking and Recognizing Arm-and-Hand Visual Signals to Aircraft},
booktitle={Proceedings of the 7th International Joint Conference on Computational Intelligence (ECTA 2015) - NCTA},
year={2015},
pages={157-162},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005630801570162},
isbn={978-989-758-157-1},
}

TY - CONF

JO - Proceedings of the 7th International Joint Conference on Computational Intelligence (ECTA 2015) - NCTA
TI - Inedited SVM Application to Automatically Tracking and Recognizing Arm-and-Hand Visual Signals to Aircraft
SN - 978-989-758-157-1
AU - Saggio, G.
AU - Cavrini, F.
AU - Di Paolo, F.
PY - 2015
SP - 157
EP - 162
DO - 10.5220/0005630801570162
PB - SciTePress