RI | Seminar | Nov 30 2007

Robotics Institute Seminar, Nov 30, 2007
Time and Place | Seminar Abstract | Speaker Biography | Speaker Appointments

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Conditional Random Fields for Labeling Tasks in Robotics

Dieter Fox

University of Washington, Seattle

Time and Place

Mauldin Auditorium (NSH 1305 )

Talk 3:30 pm

Abstract

Over the last decade, the mobile robotics community has developed highly efficient and robust solutions to estimation problems such as robot localization and map building. With the availability of various techniques for spatially consistent sensor integration, an important next goal is the extraction of high-level information from sensor data. Such information is often discrete, requiring techniques different from those typically applied to mapping and localization.

In this talk I will describe how Conditional Random Fields (CRF) can be applied to tasks such as semantic place labeling, object recognition, and scan matching. CRFs are discriminative, undirected graphical models that were developed for labeling sequence data. Due to their ability to handle arbitrary dependencies between observation features, CRFs are extremely well suited for classification problems involving high-dimensional feature vectors.

This is joint work with Bertrand Douillard, Stephen Friedman, Benson Limketkai, Lin Liao, and Fabio Ramos.

Speaker Biography

Dieter Fox is Associate Professor and Director of the Robotics and State Estimation Lab in the Computer Science & Engineering Department at the University of Washington, Seattle. He obtained his Ph.D. from the University of Bonn, Germany. Before joining UW, he spent two years as a postdoctoral researcher at the CMU Robot Learning Lab. Dieter's research focuses on probabilistic state estimation with applications in robotics and activity recognition.

Speaker Appointments

For appointments, please contact Drew Bagnell (dbagnell@ri.cmu.edu)

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The Robotics Institute is part of the School of Computer Science, Carnegie Mellon University.