TY  - JOUR
AU  - Estefania Talavera
AU  - Maria Leyva-Vallina
AU  - Md. Mostafa Kamal Sarker
AU  - Domenec Puig
AU  - Nicolai Petkov
AU  - Petia Radeva
PY  - 2020//
TI  - Hierarchical approach to classify food scenes in egocentric photo-streams
T2  - J-BHI
JO  - IEEE Journal of Biomedical and Health Informatics
SP  - 866
EP  - 877
VL  - 24
IS  - 3
N2  - Recent studies have shown that the environment where people eat can affect their nutritional behaviour. In this work, we provide automatic tools for a personalised analysis of a person's health habits by the examination of daily recorded egocentric photo-streams. Specifically, we propose a new automatic approach for the classification of food-related environments, that is able to classify up to 15 such scenes. In this way, people can monitor the context around their food intake in order to get an objective insight into their daily eating routine. We propose a model that classifies food-related scenes organized in a semantic hierarchy. Additionally, we present and make available a new egocentric dataset composed of more than 33000 images recorded by a wearable camera, over which our proposed model has been tested. Our approach obtains an accuracy and F-score of 56\% and 65\%, respectively, clearly outperforming the baseline methods.
UR  - https://ieeexplore.ieee.org/document/8735865
L1  - http://refbase.cvc.uab.es/files/TLM2020.pdf
N1  - MILAB; no proj
ID  - Estefania Talavera2020
ER  -