Title page for ETD etd-06262010-111917


Type of Document Master's Thesis
Author Kaya, Sertan
Author's Email Address sertan_kaya@yahoo.com
URN etd-06262010-111917
Title Quantification of Energy Intake Using Food Image Analysis
Degree Master of Science in Electrical Engineering (M.S.E.E.)
Department Electrical & Computer Engineering
Advisory Committee
Advisor Name Title
Gunturk, Bahadir K. Committee Chair
Chen, Jianhua Committee Member
Rai, Suresh Committee Member
Keywords
  • photogrammetry
  • camera calibration
  • food consumption estimation
  • energy intake estimation
  • gabor filter
  • food amount estimation
  • artificial neural networks
  • mahalanobis distance
  • pattern classification
Date of Defense 2010-05-19
Availability unrestricted
Abstract
Obtaining real-time and accurate estimates of energy intake while people reside in their natural environment is technically and methodologically challenging. The goal of this project is to estimate energy intake accurately in real-time and free-living conditions. In this study, we propose a computer vision based system to estimate energy intake based on food pictures taken and emailed by subjects participating in the experiment. The system introduces a reference card inclusion procedure, which is used for geometric and photometric corrections. Image classification and segmentation methods are also incorporated into the system to have fully-automated decision making.
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