Understanding Nutrition Through Machine Vision

Healthy food choices are central to nutritional security, but these choices require individuals to find a complex balance between interests in the present and future. Therefore, policies to encourage healthier eating must consider food characteristics to which people give greater attention when making these intertemporal decisions and the psychological mechanisms through which those characteristics influence the decisions. In this project, we propose to study emotion as one such psychological mechanism.

We propose to utilize cutting-edge machine vision and artificial intelligence technologies to evaluate the role of attention and emotion in food choice. These technologies use cameras to track subjects through a physical space, measure attention through eye-tracking, and measure emotion through facial micro-expressions. We propose three key research questions: 1) How do emotions mediate food choice decisions? 2) How well do emotion and attention predict food choices in a natural environment? And 3) How does emotion interact with context to influence food choice?