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Affiliation

Center of Excellence for the Acceleration of Harm Reduction, University of Catania, Via Santa Sofia 89, 95123 Catania, Italy

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1 Papers

Food Recognition for Dietary Monitoring during Smoke Quitting

Topics: Biometrics; Pattern Recognition; Texture Analysis and Classification

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

Digital Object Identifier: 10.5220/0010492701600165

Proceedings of IMPROVE 2021, ISBN: 978-989-758-511-1

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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.