CMU talk: Inferring Object Attributes

RI Seminar
Inferring Object Attributes

Derek Hoiem
Assistant Professor, University of Illinois at Urbana Champaign

April 10, 2009

Abstract: Ultimately, the goal of computer vision is to make useful inferences from imagery, and a big part of that is knowing something about the properties of nearby objects. In this talk, I'll describe our recent work on learning to identify object attributes, such as parts, materials, or shape, from images in a way that generalizes to new object categories. The tricky part is training classifiers that really predict the intended attribute, and not ones that are correlated through familiar object categories. Once we can predict attributes, we can say what is unusual about an object and more easily learn to recognize new objects Sometimes we can even recognize new object categories from a purely verbal description (e.g., a goat has four legs, horns, and is furry).

This work is with Ali Farhadi, Ian Endres, and David Forsyth at UIUC.

Speaker Bio.: Derek Hoiem is a new assistant professor at University of Illinois at Urbana Champaign. Derek researches object recognition, segmentation, 3d reconstruction from images, and other aspects of computer vision that are related to scene understanding. He recently (2007) graduated from the Robotics Institute under the tutelage of Alyosha Efros and Martial Hebert and looks forward to visiting. By request, Derek will share a little of his perspective in transitioning from being a grad student at CMU to a professor at UIUC.