Prof. Fengqing Maggie Zhu, Purdue University

June 10, 2022, 11:30am EC4-2101A

Diet is a complex exposure, measuring dietary intake presents more challenges than other environmental exposures. Image-based dietary assessment refers to the process of determining what someone eats and how much energy is consumed from visual data and associated contextual information. New, unbiased data-capture methods such as mobile dietary assessment technologies are inexpensive and customizable, which could overcome well-characterized limitations of current approaches relying primarily on self-reporting.

In this talk, I will present the design and development of a mobile, image-based dietary assessment system that records and analyzes images of eating occasions. We have developed various food image analysis methods including hierarchy based food image classification, single-view food portion size estimation, saliency-aware food image segmentation, and image-based clustering to extract eating environments. Our system has been deployed and evaluated in more than 30 dietary studies (controlled-feeding and community-dwelling) with over 2,500 participants between ages 6 months – 70 years in both domestic and international locations.