Marshall Tappen
Assistant Professor
University of Central Florida
School of Electrical Engineering and Computer Science
About Me
I am an assistant professor of computer science at the University of Central Florida
I received my PhD from MIT in 2006, SM from MIT in 2002, and BS from Brigham Young University in 2000.
Phone: (407) 823-2688
Email: mtappen at cs.ucf.edu
Address:
HEC-230
4000 Central Florida Blvd.
Orlando, FL 32817
I have openings for one or two PhD students in Fall 2010. If you are interested, please submit an application at the UCF Graduate Studies site.
Publications
2009
P. Scovanner and M.F. Tappen, Learning Pedestrian Dynamics from the Real World, To Appear
in the 2009 International Conference on Computer Vision (ICCV) [PDF]
K. G. G. Samuel and M.F. Tappen, Learning Optimized MAP Estimates in Continuously-Valued MRF Models. Appeared in The Proceedings of the 2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR) [PDF]
S. Masood, J. Zhu, and M. F. Tappen, Automatic Correction of Saturated Regions in Photographs using Cross-Channel Correlation To Appear in Pacific Graphics 2009
N. Khan and M.F. Tappen, Training Many-Parameter Shape-from-Shading Models Using a Surface Database, To Appear in the 3DIM 2009 Workshop at ICCV 2009
[PDF]
2008
M.F. Tappen, K. G.G. Samuel, C.V. Dean, and D. Lyle, The Logistic Random Field -- A Convenient Graphical Model for Learning Parameters for MRF-based Labeling. Appeared in the Proceedings of the 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR) Accepted for Oral Presentation [PDF] - Correction on complexity of gradient computation [TXT].
R. S. Szeliski, R. Zabih, D. Scharstein, O. Veksler, V. Kolmogorov, A. Agarwala, M.
Tappen, and C. Rother. "A Comparative Study of Energy Minimization Methods for Markov Random
Fields" In IEEE Transactions on Pattern Analysis and Machine Intelligence, Volume 30,
Number 6, June 2008 pp 1068-1080 [Project Page]
Brendan Moore, Marshall Tappen, and Hassan Foroosh. "Learning Face Appearance under Different Lighting Conditions " In The Second IEEE International Conference on Biometrics: Theory, Applications, and Systems. [PDF]
2007
M. F. Tappen. “Utilizing Variational Optimization to Learn
Markov Random Fields”. Appeared in The Proceedings of the 2007 IEEE Computer Society
Conference on Computer Vision and Pattern Recognition (CVPR) [PDF] -- A sample training implementation is also available [.ZIP]
M. F. Tappen, C. Liu, E. H. Adelson, and W. T. Freeman. “Learning Gaussian Conditional Random Fields for Low-Level Vision”. Appeared in The Proceedings of
the 2007 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR)
[PDF] -- A sample training implementation is also available [.ZIP] - Correction on complexity of gradient computation [TXT].
2006 and Earlier
"Learning Continuous Models for Estimating Intrinsic Component
Images", Doctoral Thesis, Massachusetts Institute of Technology, May
2006 [PDF]
M. F. Tappen, E. H. Adelson, and W. T. Freeman. “Estimating
Intrinsic Component Images using Non-Linear Regression”.
Appeared in The Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), Volume 2, Pages 1992-1999, 2006
,[PDF]
The training and test data from this paper is also available as a .MAT
file [.ZIP (10 MB)]
A Comparative Study of Energy Minimization Methods for Markov Random
Fields. Rick Szeliski, Ramin Zabih, Daniel Scharstein, Olga Veksler,
Vladimir Kolmogorov, Aseem Agarwala, Marshall Tappen, Carsten Rother.
In Seventh European Conference on Computer Vision (ECCV 2002), volume 2, pages 16-29, Graz, May 2006. Springer-Verlag.
M. F. Tappen, W. T. Freeman, and E. H. Adelson. “Recovering
Intrinsic Images from a Single Image”. In IEEE Transactions
on Pattern Analysis and Machine Intelligence, Volume 27, Issue 9,
September 2005, Pages 1459 - 1472[PDF]
M.F. Tappen, B. C. Russell, and W. T.
Freeman. “Efficient Graphical Models for Processing Images”.
The Proceedings of the 2004 IEEE Computer Society Conference on
Computer Vision and Pattern Recognition (CVPR), 2004 [PDF]
M. F. Tappen and W. T. Freeman.
“Comparison of Graph Cuts with Belief Propagation for Stereo,
using Identical MRF Parameters”. In Proceedings of the Ninth
IEEE International Conference on Computer Vision (ICCV), Pages
900 - 907, 2003 [PDF]
M. F. Tappen, B. C. Russell, and W. T.
Freeman. “Exploiting the Sparse Derivative Prior for
Super-Resolution and Image Demosaicing”. In Third
International Workshop on Statistical and Computational Theories of
Vision at ICCV 2003, 2003 [PDF]
M. F. Tappen, W. T. Freeman, and E. H.
Adelson. “Recovering Intrinsic Images from a Single Image”.
In S. T. S. Becker and K. Obermayer, editors, Advances in Neural
Information Processing Systems 15, pages 1343-1350. MIT Press,
Cambridge, MA, 2003.[PDF]
Teaching
- Fall 2008 - CAP 5415 - Computer Vision - Course Homepage (Also taught in 2006 and 2007)
- Spring 2007 - CAP 6412 - Advanced Computer Vision - Course Homepage
- Spring 2008, Fall 2008, Spring 2009 - EEL 5542 - Random Processes
Personal
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| The latest Tappen family picture (but missing our new baby girl!). I am fortunate to be married to the incomparable Joy Chan Tappen M.D. -- I married way up. |
 
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| We're thrilled to have added a little girl to the house. But it took us a bit to get used to pink! |