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A Deep learning based food recognition system for lifelog images

Nguyen, Binh T., Dang-Nguyen, Duc-Tien orcid logoORCID: 0000-0002-2761-2213, Dang, Tien X., Thai, Phat and Gurrin, Cathal orcid logoORCID: 0000-0003-2903-3968 (2018) A Deep learning based food recognition system for lifelog images. In: 7th International Conference on Pattern Recognition Applications and Methods, 16-18 Jan, 2018, Funchal, Madeira, Portugal. ISBN 978-989-758-276-9

Abstract
In this paper, we propose a deep learning based system for food recognition from personal life archive im- ages. The system first identifies the eating moments based on multi-modal information, then tries to focus and enhance the food images available in these moments, and finally, exploits GoogleNet as the core of the learning process to recognise the food category of the images. Preliminary results, experimenting on the food recognition module of the proposed system, show that the proposed system achieves 95.97% classification accuracy on the food images taken from the personal life archive from several lifeloggers, which potentially can be extended and applied in broader scenarios and for different types of food categories.
Metadata
Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Refereed:Yes
Additional Information:We would like to thank to Dr. Zaher Hinbarji from Dublin City University and Mr. Quang Pham from Singapore Management University for their valuable discussions and technical supports in the experiments.
Uncontrolled Keywords:Lifelogging; Food Recognition; CNNs; SIFT; SURF; HOG; Food Detection
Subjects:Computer Science > Lifelog
Computer Science > Machine learning
Computer Science > Information retrieval
DCU Faculties and Centres:Research Initiatives and Centres > INSIGHT Centre for Data Analytics
DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Published in: Proceedings of the 7th International Conference on Pattern Recognition Applications and Methods (ICPRAM 2018. Proceedings of the International Conference on Pattern Recognition Applications and Methods (ICPRAM) 1. Scitepress – Science and Technology Publications. ISBN 978-989-758-276-9
Publisher:Scitepress – Science and Technology Publications
Official URL:https://doi.org/10.5220/0006749006570664
Copyright Information:© 2018 SCITEPRESS
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
ID Code:22217
Deposited On:22 Jan 2018 16:21 by Duc-Tien Dang-Nguyen . Last Modified 08 Nov 2021 14:37
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