| Download | - View accepted manuscript: How much you ate? Food portion estimation on spoons (PDF, 3.7 MiB)
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| DOI | Resolve DOI: https://doi.org/10.1109/CVPRW63382.2024.00380 |
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| Author | Search for: Sharma, Aaryam; Search for: Czarnecki, Chris; Search for: Chen, Yuhao; Search for: Xi, Pengcheng1ORCID identifier: https://orcid.org/0000-0003-3236-5234; Search for: Xu, Linlin; Search for: Wong, Alexander |
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| Affiliation | - National Research Council of Canada. Digital Technologies
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| Funder | Search for: National Research Council of Canada. Aging in Place Challenge Program |
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| Format | Text, Article |
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| Conference | 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), June 17-18, 2024, Seattle, Washington, United States |
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| Subject | food; volumetric; estimation; nutrition; computer-vision |
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| Abstract | Monitoring dietary intake is a crucial aspect of promoting healthy living. In recent years, advances in computer vision technology have facilitated dietary intake monitoring through the use of images and depth cameras. However, the current state-of-the-art image-based food portion estimation algorithms assume that users take images of their meals one or two times, which can be inconvenient and fail to capture food items that are not visible from a top-down perspective, such as ingredients submerged in a stew. To address these limitations, we introduce an innovative solution that utilizes stationary user-facing cameras to track food items on utensils, not requiring any change of camera perspective after installation. The shallow depth of utensils provides a more favorable angle for capturing food items, and tracking them on the utensil’s surface offers a significantly more accurate estimation of dietary intake without the need for post-meal image capture. The system is reliable for estimation of nutritional content of liquid-solid heterogeneous mixtures such as soups and stews. Through a series of experiments, we demonstrate the exceptional potential of our method as a non-invasive, user-friendly, and highly accurate dietary intake monitoring tool. |
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| Publication date | 2024-09-27 |
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| Publisher | IEEE |
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| Licence | - © 2024 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
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| In | |
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| Language | English |
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| Peer reviewed | Yes |
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| Export citation | Export as RIS |
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| Report a correction | Report a correction (opens in a new tab) |
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| Record identifier | 0a58c89e-2b81-40e2-bf90-729fc8e58e6a |
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| Record created | 2025-01-30 |
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| Record modified | 2025-03-20 |
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