Measuring the type and amount of food intake of free-living (outside controlled clinical research centers) people
is an important task in nutrition research. One practical method, called the Remote Food Photography Method
(RFPM),1 is to provide camera-equipped smartphones to participants, who are trained to take pictures of
their foods and send these pictures to the researchers over a wireless network. These pictures can then be
analyzed by trained raters to accurately estimate food intake, though the process can be labor intensive. In this
paper, we describe a computer vision application to estimate food intake from the pictures captured and sent
by participants. We describe the application in detail, including segmentation, pattern classification, volume
estimation modules, and provide comprehensive experimental results to evaluate its performance.