Date of Award
Many people desire to be informed about the nutritional specifics of the food they consume. Current popular dietary tracking methods are too slow and tedious for a lot of consumers due to requiring manual data entry for everything eaten. We propose a system that will take advantage of image recognition and the internal camera of Android phones to identify food based off of a picture of a user’s plate. Over the course the last year, we trained an object detection model with images of different types of food, built a mobile application around it, and tested their integration and performance. We believe that our program meets the requirements we set out for it at its conception and delivers a simple, fast, and efficient way of tracking one’s diet.
Hoff, Stephen; Jaffurs, Patterson; Enriquez, Michael; and Wilde, Quintin, "Snap-n-Snack: a Food Image Recognition Application" (2018). Computer Science and Engineering Senior Theses. 121.