Fei-Fei Li : 2012 Plenary Session

 

Monday, April 2, 2012
Location: Fisher Conference Center, Arrillaga Alumni Center

"Crowds in the Cloud: Artificial Artificial Intelligence Technology"
11:15am - 11:45am

Abstract:

A most important goal of computer vision in artificial intelligence research is to develop algorithms that can recognize hundreds of thousands of objects in millions and billions of images. To achieve this goal, researchers need to work with millions and billions of images annotated with accurate labels for training and benchmarking different algorithms. Up till only a few years ago, limited by labor and money resource, computer vision scientists had been working with datasets consisted of only thousands of images annotated across a few dozen object classes. In 2008, our lab started a project called ImageNet, aiming to build the largest annotated image dataset in computer vision research. Our goal was to put together a dataset of tens of millions of images annotated with object classes found in the English dictionary (about twenty thousand of them!), an impossible mission using traditional ways of hiring subjects in university campuses. Instead we used a crowdsourcing technology to recruit tens of thousands of online workers to help us labeling more than half billion images using the Amazon Mechanical Turk platform. This talk will give a detailed account of our experience of this exciting and emerging technology and what we have done to build the largest image dataset in our research community.


Bio:

Professor Fei-Fei Li's main research interest is in vision, particularly high-level visual recognition. In computer vision, Fei-Fei's interests span from object and natural scene categorization to human activity categorizations in both videos and still images. In human vision, she has studied the interaction of attention and natural scene and object recognition, and decoding the human brain fMRI activities involved in natural scene categorization by using pattern recognition algorithms. Fei-Fei graduated from Princeton University in 1999 with a physics degree. She received PhD in electrical engineering from the California Institute of Technology in 2005. From 2005 to August 2009, Fei-Fei was an assistant professor in the Electrical and Computer Engineering Department at University of Illinois Urbana-Champaign and Computer Science Department at Princeton University, respectively. She is currently an Assistant Professor in the Computer Science Department at Stanford University since 2009. Fei-Fei is a recipient of a Microsoft Research New Faculty award, the Alfred Sloan Fellowship, a number of Google Research Award and an NSF CAREER award. (Fei-Fei publishes using the name L. Fei-Fei.)