Speaker: Daniel Huttenlocher
Cornell University
Friday, October 20, 2006
11:00 am - 12:00 pm
EBU3b 1202
ABSTRACT
Over the past few years there has been enormous progress in the development of systems that can recognize generic categories of
objects in images, such as automobiles, bicycles, airplanes, and human faces. Much of this progress can be traced to two underlying
technical advances: (i) detectors for locally invariant features of an image, and (ii) the application of techniques from machine
learning. Despite recent success, however, there are some fundamental concerns about methods that rely heavily on feature detection,
as local image evidence is often highly ambiguous due to the absence of contextual information.
We are taking a different approach to learning and recognizing visual object categories, in which there is no separate feature
detection stage. In our approach, objects are modeled as local image patches with spring-like connections that constrain the spatial
relations between patches. Such models are intuitively natural, and their use dates back over 30 years. Until recently such models
were largely abandoned due to computational challenges that are addressed by our work. Our approach can be used to learn models
from weakly labeled training data, without any specification of the location of objects or their parts. The recognition accuracy for
such models is better than when using feature-based techniques with similar forms of spatial constraint.
BIO
Dr. Daniel Huttenlocher is the John P. and Rilla Neafsey Professor of Computing,
Information Science and Business at Cornell University. His research interests are in computer vision, geometric algorithms,
interactive document systems, financial trading technology, and IT strategy. Dr. Huttenlocher has 24 U.S. patents, has published
more than 75 technical papers, was named a Presidential Young Investigator in 1990, the New York State Professor of the Year in
1993, and a Stephen H. Weiss Fellow in 1996. Dr. Huttenlocher has also served as CTO of Intelligent Markets and was on the senior
management team at Xerox PARC
