The Loop: People and Computer Vision
Andrew Gallagher, Kodak Research Labs
When we see other humans, we can quickly make judgments such as their demographic description and identity if they are familiar to us. We can answer questions related to the activities of, emotional states of, and relationships between people in an image. We draw conclusions based not just on what we see, but also from a lifetime of experience of living and interacting with other people. Even simple, common sense knowledge such as the fact hat children are smaller than adults allows us to better understand the roles of the people we see. In this work, we propose contextual features, drawn from a variety of sources, and models for understanding images of people with the objective of providing computers with access to the same contextual information that humans use.
Further, we show that computer vision and data-driven image analysis can play a role in helping us learn about people. We now are able to see millions of candid and unsolicited images of people on the Internet. Using computer vision techniques, we are able to gain insight into the lives of people, and their behavior in social situations, even their preferences for products and political candidates, that simply was not possible before. This work shows that people act in predictable ways, for example that human patterns of association contain regular structure that can be effectively modeled and learned. From a broad perspective, this work presents a loop in that our knowledge about people can help computer vision algorithms, and computer vision can help us learn more about people.
Biography: Andrew Gallagher joined Kodak Research Labs in 1996 initially working on image enhancement algorithms that became Kodak Perfect Touch, embedded in many of Kodak's consumer imaging products. Andy then went back to school, first to Rochester Institute of Technology in 2000 for an M.S., then to Carnegie Mellon University for a Ph.D. in 2009, both in electrical and computer engineering. More recently, Andy has been working with application of images of people and machine learning and is a senior principal scientist with Eastman Kodak. Andy enjoys bicycling, puzzles, whittling, games, and family.
