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Daniel
Huttenlocher of
Computing, Information Science and Business
Professor, Computer Science Department Professor, Johnson Graduate School of Management Administrative:
cis-dean “at” cs.cornell.edu |
Research
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My research
in computer vision ranges from theoretical
algorithms (using techniques from computational geometry and
graph algorithms) to the development of end-to-end
systems that apply visual matching and recognition
techniques. Some of my computer
vision work includes:
My research
on the Web and large-scale social
networks is focused on developing models and measures that allow us to
better study and understand how people interact with one another,
particularly in computer-mediated environments. For instance, how does the structure
of a social network influence one’s propensity to undertake certain
actions? There is a long history
of study of such questions in the social sciences, primarily for small-scale
networks that can be mapped out by hand.
While computer and information scientists have been studying
large-scale networks, their focus has been more on the network properties and
less on testing and extending existing social science theories of social
interaction. My work on autonomous vehicles grows out of my
role as co-leader of Team Cornell’s entry in the DARPA Urban Challenge
race. Our vehicle was one of 6
out of 11 finalists (and 35 semi-finalists) to complete the race. The students on our team made all the
design decisions and did an outstanding job overall. While the Urban Challenge and the
Grand Challenges before that have led to enormous progress in autonomous
driving, the race also highlighted some fundamental research questions that
remain to be addressed in order to enable perception and reasoning about the
actions and intentions of other vehicles. For example, the fender bender between
our vehicle and MIT’s could have been avoided if either system had been
able to perceive what the other was doing over an extended time period (i.e.,
perceive actions in addition to locations and velocities). Such issues form
the basis of my current and planned research in the area. My research
on geometric algorithms includes efficient algorithms for computing
Hausdorff distances and related distance transforms, as well as techniques
for comparing three-dimensional protein structures. My work on interactive
document systems has often incorporated computer vision techniques, and
includes:
My
interest in electronic trading systems focuses primarily on illiquid
or thinly-traded markets, where conventional auction and exchange mechanisms
are not very effective ways of making trades. My
interest in software development methodologies stems from my
involvement in the creation of large, complex software systems at Xerox
Corporation and Intelligent Markets.
Through these activities I have come to believe that: ·
We need more clearly stated principles
of software development that can help guide the choice of appropriate
development practices for a given software project. Too much of software development
methodology is aimed at practices without a deeper understanding of underlying
principles. ·
Training of software developers requires a
better understanding of the fact that software is an intellectual work
product, in many ways more akin to a legal brief, an architectural plan,
or an ad campaign, than to a physical or electronic device. As such, I believe that training
programs for software developers should be modeled more on professional
programs such as law, business, architecture or design. |
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Object
Recognition and Detection
Segmentation
and Low-Level Vision Algorithms ·
Generating Sharp Panoramas from Motion-blurred Videos, Proceedings CVPR, 2010 (with Y. Li, S.B. Kang, N. Joshi and S. Seitz). ·
Learning for Optical Flow using
Stochastic Optimization, Proceedings of European Conference on Computer
Vision (ECCV), 2008 (with Y. Li). ·
Sparse Long-Range Random Field and
its Application to Image Denoising, Proceedings of European Conference on
Computer Vision (ECCV), 2008 (with Y. Li). ·
Learning for
Stereo Vision Using the Structured Support Vector Machine, Proceedings of
the IEEE Computer Vision and Pattern Recognition Conference, 2008 (with Y.
Li). ·
Efficient
Belief Propagation with Learned Higher-Order Markov Random Fields,
Proceedings of ECCV, 2006 (with X. Lan, S. Roth and M. Black). ·
Efficient Belief
Propagation for Early Vision, to appear in Intl. Journal of Computer
Vision (with P. Felzenszwalb). Conference
version from IEEE CVPR, Vol 1, pp. 261-268, 2004. CODE ·
Efficient
Graph-Based Image Segmentation, Intl. Journal of Computer Vision,
vol. 59, no. 2, pp. 167-181, 2004 (with P. Felzenszwalb). CODE The
Web and Large-Scale Social Networks ·
Governance in Social Media:
A case study of the Wikipedia promotion process, Proceedings of AAAI International Conference on Weblogs and Social Media (ICWSM)
2010 (with
J. Leskovec and J. Kleinberg). ·
Predicting Positive and Negative Links in Online Social Networks, Proceedings of Nineteenth International World Wide Web Conference (WWW)
2010 (with
J. Leskovec and J. Kleinberg). ·
Signed Networks in Social Media, Proceedings of ACM CHI 2010 (with
J. Leskovec and J. Kleinberg). ·
Mapping the World's Photos, Proceedings of Eighteenth International World Wide Web Conference (WWW)
2009 (with
D. Crandall, L. Backstrom and J. Kleinberg). ·
Feedback Effects between Similarity and
Social Influence in Online Communities, Proceedings
of Fourteenth ACM Conference on Knowledge Discovery and Data Mining (KDD)
2008 (with
D. Crandall, D. Cosley, J. Kleinberg and ·
Group Formation in Large Social Networks:
Membership, Growth, and Evolution, Proceedings of Twelfth ACM Conference on Knowledge Discovery and Data Mining KDD (with
L. Backstrom, J. Kleinberg and X. Lan), 2006. ·
Traffic-Based
Feedback on the Web. Proceedings of the ·
Fast
Algorithms for Large State Space HMM’s with Applications to Web Usage
Analysis, Advances in Neural Information Processing Systems (NIPS) 16,
December 2003 (with P. Felzenszwalb and J. Kleinberg). Tracking
Geometric
Algorithms
Interactive
Document Systems
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·
Structured Models in Computer Vision, Workshop on Structured Models at CVPR 2010 ·
Social Data, HICSS-43 Keynote talk, 2010 ·
Tutorial
on Pictorial Structures, ICVSS 2009 ·
Mapping the
World’s Photos: Communal Perception, ETHZ, EPFL, ENS 2009 ·
Team Cornell’s
Entry in DARPA Urban Challenge, 2007-08 (video of Google Techtalk) ·
Object
Recognition Without Feature Detection, Oxford 2007. ·
Speeding Up Belief
Propagation for Early Vision, MSRI Workshop, Feburary 2005 |
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In the past
I have taught CS3110,
functional programming and data structures, NBA6000 on the strategic role of
information technology and NBA6100 on the management of technology-driven
businesses using bio, info and nano technologies (jointly with Bruce
Ganem). I last taught
computer vision in Spring 2008, CS664. |
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Professional
Activities |
For
many years (1988-1999) I worked with Xerox PARC on electronic document image
processing. More recently I have
been working with Intelligent Markets on
electronic trading systems. In
1998-99 I chaired the Cornell Task Force on Computing and Information, which
led to the creation of the Faculty of Computing
and Information Science. In
2005-06 I also chaired the Cornell Task Force on Wisdom in the
Age of Information. I was
general co-chair for CVPR 2009 in Miami and CVPR in 2006 in NYC as well as
program co-chair of CVPR in 2001 and 1997 (CVPR is the main North
American computer vision conference). I serve on the Board of Directors of the MacArthur Foundation, which has reinforced my view of the important role for information
technology in achieving social good. |
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Other
Interests |
My
favorite non-computer-geek activity is snowboarding (but without the
mtv-extreme-sports-way-too-cool attitude). |
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Last
Updated: August 2010 |
