Ulster University Logo

Semi-automated system for predicting calories in photographs of meals

McAllister, Patrick, Zheng, Huiru, Bond, Raymond and Moorhead, Anne (2015) Semi-automated system for predicting calories in photographs of meals. In: IEEE International Conference on Engineering, Technology and Innovation/ International Technology Management Conference, Belfast. IEEE. 6 pp. [Conference contribution]

Full text not available from this repository.

URL: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7438668&searchWithin=%22Authors%22:.QT.Patrick%20McAllister.QT.&newsearch=true

DOI: 10.1109/ICE.2015.7438668


Obesity is increasing globally. Obesity brings with it many chronic conditions. There has been increasing research in the use of ICT interventions to combat obesity using food logging and image calorie analysis. These interventions allow users to document their calorie intake to help promote healthy living. However using food logs may lead to inaccurate readings as the user may incorrectly calculate portion size when recording nutritional information. This paper discusses the use of image nutritional analysis techniques to ascertain a more accurate calorie reading from photographs of food items. The methods employed involve determining a ground truth data set by correlating weight of a food item with its area in cm2. This dataset could then be plotted on a regression model and used to determine calorie content of future portions. The proposed system uses a semi-automated approach to allow users to manually draw around the food portion using a polygonal tool. Results show that the application achieved a reasonable accuracy in predicting the calorie content of food item portions with a 11.82% percentage error.

Item Type:Conference contribution (Speech)
Keywords:machine learning, machine vision, obesity, nutrition, self-management
Faculties and Schools:Faculty of Social Sciences > School of Communication
Faculty of Computing & Engineering
Faculty of Computing & Engineering > School of Computing and Mathematics
Faculty of Social Sciences
Research Institutes and Groups:Institute for Research in Social Sciences > Communication
Computer Science Research Institute > Smart Environments
Computer Science Research Institute
Institute for Research in Social Sciences
ID Code:34548
Deposited By: Dr Raymond Bond
Deposited On:28 Apr 2016 09:58
Last Modified:28 Apr 2016 09:58

Repository Staff Only: item control page