Volumetric Food Quantification Using Computer Vision on a Depth-Sensing Smartphone: Preclinical Study
JMIR mhealth and uhealth2019Vol. 8(3), pp. e15294–e15294
Citations Over TimeTop 12% of 2019 papers
David Herzig, Christos T. Nakas, Janine Stalder, Christophe Kosinski, Céline Laesser, Joachim Dehais, Raphael Jaeggi, Alexander Leichtle, Fried-Michael Dahlweid, Christoph Stettler, Lia Bally
Abstract
This study evaluated the accuracy of a novel smartphone app with an integrated depth-sensing camera and found highly accurate volume estimation across a broad range of food items. In addition, the system demonstrated high segmentation performance and low processing time, highlighting its usability.
Related Papers
- → Variation in the Oral Processing of Everyday Meals Is Associated with Fullness and Meal Size; A Potential Nudge to Reduce Energy Intake?(2016)84 cited
- → The effect of television watching and portion size on intake during a meal(2017)11 cited
- → Does the cost of a meal influence the portion size effect?(2018)19 cited
- → Effects of changes in portion size on meal eating behaviour in overweight women(2013)
- → Gender Differences in Estimating Before and After a Meal(2013)