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Authors: Sebastiano Battiato 1 ; Pasquale Caponnetto 2 ; Oliver Giudice 1 ; Mazhar Hussain 1 ; Roberto Leotta 1 ; Alessandro Ortis 1 and Riccardo Polosa 2

Affiliations: 1 Department of Mathematics and Computer Science, University of Catania, Viale A. Doria, 6, 95125 Catania, Italy ; 2 Center of Excellence for the Acceleration of Harm Reduction, University of Catania, Via Santa Sofia 89, 95123 Catania, Italy

Keyword(s): Food Recognition, Dietary Monitoring, AI for Health Applications.

Abstract: This paper presents the current state of an ongoing project which aims to study, develop and evaluate an automatic framework able to track and monitor the dietary habits of people involved in a smoke quitting protocol. The system will periodically acquire images of the food consumed by the users, which will be analysed by modern food recognition algorithms able to extract and infer semantic information from food images. The extracted information, together with other contextual data, will be exploited to perform advanced inferences and to make correlations between eating habits and smoke quitting process steps, providing specific information to the clinicians about the response to the quitting protocol that are directly related to observable changes in eating habits.

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Paper citation in several formats:
Battiato, S.; Caponnetto, P.; Giudice, O.; Hussain, M.; Leotta, R.; Ortis, A. and Polosa, R. (2021). Food Recognition for Dietary Monitoring during Smoke Quitting. In Proceedings of the International Conference on Image Processing and Vision Engineering - IMPROVE; ISBN 978-989-758-511-1, SciTePress, pages 160-165. DOI: 10.5220/0010492701600165

@conference{improve21,
author={Sebastiano Battiato. and Pasquale Caponnetto. and Oliver Giudice. and Mazhar Hussain. and Roberto Leotta. and Alessandro Ortis. and Riccardo Polosa.},
title={Food Recognition for Dietary Monitoring during Smoke Quitting},
booktitle={Proceedings of the International Conference on Image Processing and Vision Engineering - IMPROVE},
year={2021},
pages={160-165},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010492701600165},
isbn={978-989-758-511-1},
}

TY - CONF

JO - Proceedings of the International Conference on Image Processing and Vision Engineering - IMPROVE
TI - Food Recognition for Dietary Monitoring during Smoke Quitting
SN - 978-989-758-511-1
AU - Battiato, S.
AU - Caponnetto, P.
AU - Giudice, O.
AU - Hussain, M.
AU - Leotta, R.
AU - Ortis, A.
AU - Polosa, R.
PY - 2021
SP - 160
EP - 165
DO - 10.5220/0010492701600165
PB - SciTePress

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