Eye Movements and Food Choice

Project Summary

Biomedical Engineering and Electrical and Computer Engineering major David Brenes, and Electrical and Computer Engineering/Computer Science majors Xingyu Chen and David Yang spent ten weeks working with mobile eye tracker data to optimize data processing and feature extraction. They generated their own video data with SMI Eye Tracking Glasses, and created computer vision algorithms to categorize subject gazing behavior in a grocery purchase decision-making environment.

Themes and Categories
Health, Public Policy
Data+
Year
2016

Project Results

The team created feature extraction algorithms using Scale-Invariant Feature Transform (SIFT) and Fast Approximate Nearest Neighbor Search Library (FLANN) computer vision techniques implemented in OpenCV and Python, greatly reducing the manual data processing bottleneck for researchers.

Download the Executive Summary (PDF)

Video Introduction to the Eye Movement and Food Choice Project

Faculty Sponsor

Project Managers

Disciplines Involved

  • Psychology
  • Neuroscience
  • All quantitative STEM

Participants

  • David Brenes, Duke University Biomedical Engineering & Electrical and Computer Engineering
  • David Yang, Duke University Electrical and Computer Engineering & Computer Science
  • Xingyu Chen, Duke University Electrical and Computer Engineering & Computer Science

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