FOODCAM: A Novel Structured Light-Stereo Imaging System for Food Portion Size Estimation
Imaging-based methods of food portion size estimation (FPSE) promise higher accuracies compared to traditional methods. Many FPSE methods require dimensional cues (fiducial markers, finger-references, object-references) in the scene of interest and/or manual human input (wireframes, virtual models)....
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2022-04-01
|
| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/22/9/3300 |
| _version_ | 1797502830431436800 |
|---|---|
| author | Viprav B. Raju Edward Sazonov |
| author_facet | Viprav B. Raju Edward Sazonov |
| author_sort | Viprav B. Raju |
| collection | DOAJ |
| description | Imaging-based methods of food portion size estimation (FPSE) promise higher accuracies compared to traditional methods. Many FPSE methods require dimensional cues (fiducial markers, finger-references, object-references) in the scene of interest and/or manual human input (wireframes, virtual models). This paper proposes a novel passive, standalone, multispectral, motion-activated, structured light-supplemented, stereo camera for food intake monitoring (FOODCAM) and an associated methodology for FPSE that does not need a dimensional reference given a fixed setup. The proposed device integrated a switchable band (visible/infrared) stereo camera with a structured light emitter. The volume estimation methodology focused on the 3-D reconstruction of food items based on the stereo image pairs captured by the device. The FOODCAM device and the methodology were validated using five food models with complex shapes (banana, brownie, chickpeas, French fries, and popcorn). Results showed that the FOODCAM was able to estimate food portion sizes with an average accuracy of 94.4%, which suggests that the FOODCAM can potentially be used as an instrument in diet and eating behavior studies. |
| first_indexed | 2024-03-10T03:41:45Z |
| format | Article |
| id | doaj.art-2e2e3f03077e46b98cbc6380af44cae9 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T03:41:45Z |
| publishDate | 2022-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-2e2e3f03077e46b98cbc6380af44cae92023-11-23T09:16:25ZengMDPI AGSensors1424-82202022-04-01229330010.3390/s22093300FOODCAM: A Novel Structured Light-Stereo Imaging System for Food Portion Size EstimationViprav B. Raju0Edward Sazonov1Department of Electrical & Computer Engineering, The University of Alabama, Tuscaloosa, AL 35487, USADepartment of Electrical & Computer Engineering, The University of Alabama, Tuscaloosa, AL 35487, USAImaging-based methods of food portion size estimation (FPSE) promise higher accuracies compared to traditional methods. Many FPSE methods require dimensional cues (fiducial markers, finger-references, object-references) in the scene of interest and/or manual human input (wireframes, virtual models). This paper proposes a novel passive, standalone, multispectral, motion-activated, structured light-supplemented, stereo camera for food intake monitoring (FOODCAM) and an associated methodology for FPSE that does not need a dimensional reference given a fixed setup. The proposed device integrated a switchable band (visible/infrared) stereo camera with a structured light emitter. The volume estimation methodology focused on the 3-D reconstruction of food items based on the stereo image pairs captured by the device. The FOODCAM device and the methodology were validated using five food models with complex shapes (banana, brownie, chickpeas, French fries, and popcorn). Results showed that the FOODCAM was able to estimate food portion sizes with an average accuracy of 94.4%, which suggests that the FOODCAM can potentially be used as an instrument in diet and eating behavior studies.https://www.mdpi.com/1424-8220/22/9/3300food portionportion size estimationfood volumefood imagingdietary assessment |
| spellingShingle | Viprav B. Raju Edward Sazonov FOODCAM: A Novel Structured Light-Stereo Imaging System for Food Portion Size Estimation Sensors food portion portion size estimation food volume food imaging dietary assessment |
| title | FOODCAM: A Novel Structured Light-Stereo Imaging System for Food Portion Size Estimation |
| title_full | FOODCAM: A Novel Structured Light-Stereo Imaging System for Food Portion Size Estimation |
| title_fullStr | FOODCAM: A Novel Structured Light-Stereo Imaging System for Food Portion Size Estimation |
| title_full_unstemmed | FOODCAM: A Novel Structured Light-Stereo Imaging System for Food Portion Size Estimation |
| title_short | FOODCAM: A Novel Structured Light-Stereo Imaging System for Food Portion Size Estimation |
| title_sort | foodcam a novel structured light stereo imaging system for food portion size estimation |
| topic | food portion portion size estimation food volume food imaging dietary assessment |
| url | https://www.mdpi.com/1424-8220/22/9/3300 |
| work_keys_str_mv | AT vipravbraju foodcamanovelstructuredlightstereoimagingsystemforfoodportionsizeestimation AT edwardsazonov foodcamanovelstructuredlightstereoimagingsystemforfoodportionsizeestimation |