research-article

Open access

Survey on food intake methods using visual technologies

Authors:

Sudhir Kumar Dubey,

Nicola Drueeke,

Gerald BieberAuthors Info & Claims

iWOAR '23: Proceedings of the 8th international Workshop on Sensor-Based Activity Recognition and Artificial Intelligence

Article No.: 5, Pages 1 - 11

https://doi.org/10.1145/3615834.3615839

Published: 11 October 2023 Publication History

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Abstract

Assessing food intake is important for reasons of well-being, lifestyle, health, appearance, or fun. Particularly in the field of medicine, the intake of appropriate foods and quantities of food is considered elementary and always related to physical activity. Various food tracking techniques exist, ranging from pen-based, purchase-based, calorie-counting to camera-based systems. Here, it is important that automated systems can recognize ingredients and estimate quantities. Therefore, there are many camera-based systems, but they differ in terms of accuracy, speed or performance. This review provides an overview of existing technologies and describes new approaches in the area of volume-sensitive sensing methods using lidar and true-depth technologies.

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Lin CHuang J(2024)Nutrient Intake Estimation System Integrating Semantic Segmentation and Point Cloud Modeling Techniques2024 IEEE 4th International Conference on Electronic Communications, Internet of Things and Big Data (ICEIB)10.1109/ICEIB61477.2024.10602591(539-543)Online publication date: 19-Apr-2024
https://doi.org/10.1109/ICEIB61477.2024.10602591

Index Terms

Survey on food intake methods using visual technologies
1. Applied computing
  1. Life and medical sciences
    1. Consumer health
    2. Health care information systems
2. Computing methodologies
  1. Artificial intelligence

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cover image ACM Other conferences

iWOAR '23: Proceedings of the 8th international Workshop on Sensor-Based Activity Recognition and Artificial Intelligence

September 2023

171 pages

ISBN:9798400708169

DOI:10.1145/3615834

Copyright © 2023 Owner/Author.

This work is licensed under a Creative Commons Attribution International 4.0 License.

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Association for Computing Machinery

New York, NY, United States

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Published: 11 October 2023

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iWOAR 2023

iWOAR 2023: 8th international Workshop on Sensor-Based Activity Recognition and Artificial Intelligence

September 21 - 22, 2023

Lübeck, Germany

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Overall Acceptance Rate 46 of 73 submissions, 63%

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Cited By

Lin CHuang J(2024)Nutrient Intake Estimation System Integrating Semantic Segmentation and Point Cloud Modeling Techniques2024 IEEE 4th International Conference on Electronic Communications, Internet of Things and Big Data (ICEIB)10.1109/ICEIB61477.2024.10602591(539-543)Online publication date: 19-Apr-2024
https://doi.org/10.1109/ICEIB61477.2024.10602591

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