Trevor Darrell

Trevor Darrell

CS Division, University of California, Berkeley, CA, and the

International Computer Science Institute, Berkeley, CA.

Prof. Darrell leads the newly formed Computer Vision Group at the International Computer Science Institute, and is on the faculty of the CS Division at UC Berkeley. His group develops algorithms to enable multimodal conversation with robots and mobile devices, and methods for object and activity recognition on such platforms. His interests include computer vision, machine learning, computer graphics, and perception-based human computer interfaces. Prof. Darrell was on the faculty of the MIT EECS department from 1999-2008, where he directed the Vision Interface Group. He was a member of the research staff at Interval Research Corporation from 1996-1999, and received the S.M., and PhD. degrees from MIT in 1992 and 1996, respectively. He obtained the B.S.E. degree from the University of Pennsylvania in 1988, having started his career in computer vision as an undergraduate researcher in Ruzena Bajcsy's GRASP lab.

Current Teaching

CS280 Introduction to Computer Vision (Fall 2009)

CS294 Object Recognition Seminar (Spring 2009)

Recent Presentation

Invited talk given at 2009 Bay Area Vision Meeting

Invited talk given at IUI 2009

Recent Publications

1. M. Fritz, M. Black, G. Bradski, and T. Darrell, An Additive Latent Feature Model for Transparent Object Recognition, NIPS 2009, to appear.

2. B. Kulis and T. Darrell, Learning to Hash with Binary Reconstructive Embeddings, NIPS 2009, to appear.

3. K. Saenko and T. Darrell, Filtering Abstract Senses From Image Search Results, NIPS 2009, to appear.

4. A. Kapoor, K. Grauman, R. Urtasun, and T. Darrell, Gaussian Processes for Object Categorization, IJCV, to appear (preprint).

5. A. Quattoni, X. Carreras, M. Collins, and T. Darrell, An Efficient Projection for L-1/L-Infinity Regularization, ICML 2009.

6. T. Yeh and T. Darrell, “Fast Concurrent Object Localization and Recognition”, 8pp., Conference on Computer Vision and Pattern Recognition, CVPR 2009.

7. M. Christoudias, R. Urtasun, A. Kapoor and T. Darrell, “Co-training with Noisy Perceptual Observations”, 8 pp., Conference on Computer Vision and Pattern Recognition, CVPR 2009.

8. A. Geiger, R. Urtasun, and T. Darrell, “Rank Priors for Continuous Non-Linear Dimensionality Reduction”, 8 pp., Conference on Computer Vision and Pattern Recognition, CVPR 2009.

9. M. Frampton, Raquel Fernandez, Patrick Ehlen, Mario Ehlen, Mario Christoudias, Trevor Darrell and Stanley Peters (2009) “Who is ``You"? Combining Linguistic and Gaze Features to Resolve Second-Person References in Dialogue” To appear in Proceedings of EACL'09, Athens, Greece

10. K. Saenko, and T. Darrell, "Unsupervised Learning of Visual Sense Models for Polysemous Word”, Proc. NIPS 2008, 8 pp., Vancouver, Canada, December 2008.

11. T. Yeh, J. Lee, and T. Darrell, “Photo-based Question Answering”, ACM Multimedia 2008, Pages 389-398, Vancouver, Canada, October 2008,

12. T. Yeh, and T. Darrell, “Multimodal Question Answering for Mobile Devices”, IUI 2008 (short paper), Pages 405-408, ACM, 2008

13. M. Christoudias, R. Urtasun and T. Darrell, “Multi-View Learning in the Presence of View Disagreement”, 9 pp., In Proceedings of the Conference on Uncertainty in Artificial Intelligence (UAI), 2008.

14. R. Urtasun, D. J. Fleet, A. Geiger, J. Popovic, T. Darrell and N. D. Lawrence, “Topologically-Constrained Latent Variable Models”, In International Conference in Machine Learning (ICML), pp. 104-118, Helsinki, Finland, July 2008

15. M. Christoudias, R. Urtasun and T. Darrell, “Unsupervised Feature Selection via Distributed Coding for Multi-view Object Recognition”, 8pp., Conference on Computer Vision and Pattern Recognition CVPR 2008, Anchorage, AK, June 2008

16. A. Quattoni, M. Collins, and T. Darrell, “Transfer Learning for Image Classification with Sparse Prototype Representations”, 8 pp., Conference on Computer Vision and Pattern Recognition CVPR 2008, Anchorage, AK, June 2008

17. T. Yeh, J. Lee, and T. Darrell, “Dynamic Visual Category Learning”, 8 pp., Conference on Computer Vision and Pattern Recognition CVPR 2008, Anchorage, AK, June 2008

18. R. Urtasun, and T. Darrell, “Sparse probabilistic regression for activity-independent human pose inference”. 8 pp., Conference on Computer Vision and Pattern Recognition CVPR 2008, Anchorage, AK, June 2008

19. T. Yeh, J. Lee, and T. Darrell, “Scalable classifiers for Internet vision tasks”, IEEE Workshop on Internet Vision, 8 pp., Anchorage, AK, June 2008

20. Z. Stone, T. Zickler, and T. Darrell, “Autotagging Facebook: Social Network Context Improves Photo Annotation”, IEEE Workshop on Internet Vision, 8 pp., Anchorage, AK, June 2008. (Best Paper Award.)

(Full Publication List)

ICSI/UCB Vision Group

Current Postdocs:

Dr. Mario Fritz (PhD: TU Darmstadt)

Dr. Mathieu Salzmann (PhD: EPFL)

Dr. Brian Kulis (PhD: UT Austin)

Dr. Mario Christhoudias (PhD: MIT)

Dr. Kate Saenko (PhD: MIT)

Dr. Carl Henrik Ek (PhD: Oxford Brookes)

Current PhD Students:

Ashley Eden (UCB)

Alex Shyr (UCB)

Dave Golland (UCB)

Trevor Owens (UCB)

Sergey Karayev (UCB)

Graduated PhD. Students:

Mario Christoudas, Probabilistic Models for Semi-Supervised Learning and Coding, Aug 2009 [Postdoc, UCB/ICSI]

Kate Saenko, Image Sense Disambiguation: A Multimodal Approach, Aug 2009 [Postdoc UCB/ICSI]

Tom Yeh, Interacting with Computers using Images for Search and Automation, May 2009 [Postdoc, UMD]

Ariadna Quattoni, Transfer Learning Algorithms for Image Classification, May 2009 [Postdoc, Barcelona]

Sy Bor Wang, Communication Error Detection Using Facial Expressions, May 2008 [Research Scientist, Trimble Navigations]

Louis-Philippe Morency, Dialogue Context and Visual Gesture Recognition, Oct 2006 [Research Scientist, USC]

Kristen Grauman, Matching sets of features for efficient retrieval and recognition, Aug. 2006 [Assistant Professor, CS, University of Texas, Austin]

Leonid Taycher, Statistical methods for dynamic visual processing, Aug 2006 [Google Boston]

Kevin Wilson, Learning Uncertainty Models for Audiovisual Speech Source Localization in Real-World Environments, Aug 2006 [Research Scientist, MERL]

Gregory Shakhnarovich, Learning Features for Visual Classification, Oct. 2005 [Assistant Professor, TTI-C]

Ali Rahimi, Learning to Transform Time Series with a Few Examples, Oct. 2005 [Intel Research Laboratories, Seattle]

Previous Classes:

Fall 2009 (Berkeley): CS280: Computer Vision

Spring 2009 (Berkeley): CS294-43: Object Recognition Seminar

Spring 2007: 6.870: Intelligent Multimodal Interfaces

Spring 2006: 6.001 Lectures

Fall 2005: 6.897 Object Recognition Seminar

Spring 2005: 6.001 Lectures

Fall 2004: 6.001 Recitation

Spring 2004: 6.891 Computer Vision and Applications

Fall 2002: 6.801/6.866 Computer Vision

Spring 2002: 6.001 Recitation

Fall 2001: (6.892) Computer Vision for Interface and Surveillance: Algorithms and Implications

Spring 2001: 6.001 Recitation

Fall 2000: (6.892) Computer Vision for Interface and Surveillance: Algorithms and Implications

Spring 2000: Vision Interface Reading Group.

Spring 2000: 6.001 Recitation

(Stanford) Spring 1997: CS377B; Machine Perception for Human-Computer Interface, under Terry Winograd's PCD program in the Department of Computer Science.