Dean and Vice Provost
Daniel Huttenlocher is the Dean and Vice Provost of Cornell Tech. As Dean, he has overall responsibility for programmatic aspects of the new campus, including the academic quality and direction of the campus’ degree programs and research. Working with both internal and external stakeholders, he is developing strategic plans for the most effective ways of working with companies and early stage investors in New York City as well as overseeing the faculty recruitment and entrepreneurial initiatives of the campus. Huttenlocher has a mix of academic and industry background, having worked at the Xerox Palo Alto Research Center (PARC) and served as CTO of Intelligent Markets, as well as being a faculty member at Cornell for two decades. He received his bachelor’s degree from the University of Michigan and both his Master’s and Doctorate degree from Massachusetts Institute of Technology (MIT); and currently serves as a Trustee of the John D. and Catherine T. MacArthur Foundation.
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- Title and Contact Info
Daniel P. Huttenlocher
- Dean and Vice Provost, Cornell Tech
- Professor, Computer Science Department
- Professor, Johnson Graduate School of Management
- John P. and Rilla Neafsey Professor of Computing, Information Science and Business
- Stephen H. Weiss Fellow
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:
- Image matching and comparison
- Graphical models for object recognition – a Bayesian approach to object recognition that takes into account local spatial dependencies among features (implementations are available for several papers, see below)
- Pictorial structures for recognizing generic objects composed of multiple parts, such as people and faces
- Hausdorff-based methods for visual matching and recognition (an old C implementation for SunOS is also available)
- Performance evaluation and modeling of recognition methods
- Object tracking and video monitoring
- Object tracking and identification in video
- Video surveillance and monitoring for detecting vehicles in built-up areas
- Pictorial structure models for tracking people
- Fast loopy belief propagation for stereo, motion and image restoration (a C++ implementation is available)
- Segmentation using local variation (a C++ implementation is available)
- Efficient algorithms for low-level vision
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:
- DigiPaper: a highly compact, universally viewable document image format (now the Silx project at PARC)
- CoNote: a system for supporting collaboration with shared documents
- Automatically constructing browse-able presentations from a video recording of a lecture
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.
- Image matching and comparison
- Selected Papers
OBJECT RECOGNITION AND DETECTION
- Location Recognition Using Prioritized Feature matching, Proceedings of ECCV, 2010 (with Y. Li and N. Snavely).
- Landmark Classification in Large-scale Image Collections, Proceedings of IEEE ICCV, 2009 (with Y. Li and D. Crandall).
- Composite Models of Objects and Scenes for Category Recognition, Proceedings of IEEE CVPR, 2007 (with D. Crandall).
- Weakly Supervised Learning of Part-Based Spatial Models for Visual Object Recognition, Proceedings of ECCV, 2006 (with D. Crandall). CODE
- Beyond Trees: Common Factor Models for 2D Human Pose Recovery, Proceedings of IEEE ICCV, pp. 470-477, 2005 (with X. Lan).
- Spatial Priors for Part-Based Recognition Using Statistical Models, Proceedings of IEEE CVPR, 2005 (with D. Crandall and P. Felzenszwalb). CODE
- Pictorial Structures for Object Recognition, Intl. Journal of Computer Vision, 61(1), pp. 55-79, January 2005 (with P. Felzenszwalb).
- Object Recognition Using Subspace Methods, IEEE Trans. on Pattern Analysis and Machine Intelligence, vol. 21, no. 9, pp. 951-956, 1999 (with R. Lilien and C. Olson).
- A New Bayesian Approach to Object Recognition, Proceedings of IEEE CVPR, pp. 517-523, 1999 (with Y. Boykov).
- Automatic Target Recognition by Matching Oriented Edge Pixels, IEEE Trans. on Image Processing, vol. 6, no. 1, pp. 103-113, 1997 (with C. Olson).
- Comparing Images Using the Hausdorff Distance, IEEE Trans. on Pattern Analysis and Machine Intelligence, vol. 15, no. 9, pp. 850-863, 1993 (with G. Klanderman and W. Rucklidge).
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 S. Suri).
- 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 National Academy of Sciences, 6 January 2004 (with J. Aizen, J. Kleinberg and T. Novak).
- 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).
- Long Term Arm and Hand Tracking for Continuous Sign Language TV Broadcasts, Proceedings of BMVC, 2008 (with P. Buehler, M. Everingham and A. Zisserman).
- A Unified Spatio-Temporal Articulated Model for Tracking, Proceedings of IEEE CVPR, Vol. I, pp. 722-729, 2004 (with X. Lan).
- Adaptive Bayesian Recognition in Tracking Rigid Objects, Proceedings of IEEE CVPR, pp. 697-704, 2000 (with Y. Boykov).
- Tracking Nonrigid Objects in Complex Scenes, Proceedings of ICCV, pp. 93-101, 1993 (with J.J. Noh and W.J. Rucklidge).
- Distance Transforms of Sampled Functions, Cornell Computing and Information Science Technical Report TR2004-1963, September 2004. (with P. Felzenszwalb). CODE
- Fast Detection of Common Geometric Substructure in Proteins, Journal of Computational Biology, Vol 6, No. 3, pp. 313-325, 1999 (with L.P. Chew, K. Kedem and J. Kleinberg).
INTERACTIVE DOCUMENT SYSTEMS
- On DigiPaper and the Dissemination of Electronic Documents, D-Lib Magazine, Vol. 6, No. 1, January 2000 (with A. Moll).
- Document-centered peer collaborations: An exploration of educational uses of networked communication technologies, Journal of Computer Mediated Communication, vol. 4, no. 3, 1999 (with G. Gay, A. Sturgill, W. Martin).
- Digipaper: A versatile color image representation, Proceedings of ICIP, Kobe, Japan, vol. 1, pp 219-223, 1999 (with P. Felzenszwalb, W. Rucklidge).
- Selected Talks
- 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
- Professional Activities
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.