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Image-Based Volume Estimation for Food in a Bowl.

Wenyan Jia1, Boyang Li1, Qi Xu2

  • 1Department of Electrical and Computer Engineering, University of Pittsburgh, Pittsburgh, PA, USA.

Journal of Food Engineering
|January 19, 2026
PubMed
Summary
This summary is machine-generated.

Estimating food volume from images is difficult. This study introduces a Food Area Ratio (FAR) method to accurately measure food volume in bowls using 2D images, improving dietary monitoring.

Keywords:
Bowl shapeFood volume estimationImage-assisted dietary assessment

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Area of Science:

  • Nutrition science
  • Computer vision
  • Food science

Background:

  • Image-assisted dietary assessment is increasingly used for monitoring.
  • Estimating food volume from 2D images is challenging due to lack of 3D data and occlusion.
  • Accurate food volume estimation is crucial for precise dietary intake analysis.

Purpose of the Study:

  • To develop a method for accurate food volume estimation in bowls using 2D images.
  • To investigate the relationship between observable food surface and bowl fullness.
  • To establish a reliable food volume assessment technique for dietary studies.

Main Methods:

  • A mathematical model was created to describe various bowl shapes.
  • An experimental method was proposed for determining bowl geometry.
  • A Food Area Ratio (FAR) was developed to quantify food volume from images.

Main Results:

  • A strong correlation was found between bowl fullness and the calculated FAR.
  • Simulations and real-world experiments validated the proposed approach.
  • The FAR method demonstrated feasibility and accuracy in estimating food volume.

Conclusions:

  • The proposed FAR method offers a viable solution for estimating food volume in bowls.
  • This technique can enhance the accuracy of image-assisted dietary assessments.
  • The approach addresses limitations of 2D imaging in food volume quantification.