| Song, Hyun Oh, Girshick, Ross, Zickler, Stefan, Geyer, Christopher, Felzenszwalb, Pedro, Darrell, Trevor Generalized Sparselet Models for Real-Time Multiclass Object Recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence. 2015; 37 (5) : 1001-1012. |
| Felzenszwalb, Pedro, Girshick, Ross, McAllester, David, Ramanan, Deva Visual object detection with deformable part models. Communications of the ACM. 2013; 56 (9) : 97. |
| Pedro F. Felzenszwalb, Daniel P. Huttenlocher Distance Transforms of Sampled Functions. Theory of Computing. 2012; 8 (19) : 415-428. |
| Parizi, S. N., Oberlin, J. G., Felzenszwalb, P. F. Reconfigurable models for scene recognition. 2012 IEEE Conference on Computer Vision and Pattern Recognition. 2012; |
| Song, Hyun Oh, Zickler, Stefan, Althoff, Tim, Girshick, Ross, Fritz, Mario, Geyer, Christopher, Felzenszwalb, Pedro, Darrell, Trevor Sparselet Models for Efficient Multiclass Object Detection. Automata, Languages and Programming. 2012; : 802-815. |
| Felzenszwalb, P F, Zabih, R Dynamic Programming and Graph Algorithms in Computer Vision. IEEE Transactions on Pattern Analysis and Machine Intelligence. 2011; 33 (4) : 721-740. |
| Felzenszwalb, Pedro F., McAuley, J. J. Fast Inference with Min-Sum Matrix Product. IEEE Transactions on Pattern Analysis and Machine Intelligence. 2011; 33 (12) : 2549-2554. |
| Felzenszwalb, Pedro F., Girshick, Ross B., McAllester, David Cascade object detection with deformable part models. 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 2010; |
| Felzenszwalb, Pedro F., Pap, Gyula, Tardos, Eva, Zabih, Ramin Globally optimal pixel labeling algorithms for tree metrics. 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 2010; |
| Felzenszwalb, P F, Girshick, R B, McAllester, D, Ramanan, D Object Detection with Discriminatively Trained Part-Based Models. IEEE Transactions on Pattern Analysis and Machine Intelligence. 2010; 32 (9) : 1627-1645. |
| Felzenszwalb, Pedro F., Veksler, Olga Tiered scene labeling with dynamic programming. 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 2010; |
| Babai, László, Felzenszwalb, Pedro F. Computing rank-convolutions with a mask. ACM Transactions on Algorithms. 2009; 6 (1) : 1-13. |
| Basri, R., Felzenszwalb, P.F., Girshick, R.B., Jacobs, D.W., Klivans, C.J. Visibility constraints on features of 3D objects. 2009 IEEE Conference on Computer Vision and Pattern Recognition. 2009; |
| Felzenszwalb, Pedro, McAllester, David, Ramanan, Deva A discriminatively trained, multiscale, deformable part model. 2008 IEEE Conference on Computer Vision and Pattern Recognition. 2008; |
| Felzenszwalb, Pedro F., Schwartz, Joshua D. Hierarchical Matching of Deformable Shapes. 2007 IEEE Conference on Computer Vision and Pattern Recognition. 2007; |
| Felzenszwalb, P., McAllester, D. A Min-Cover Approach for Finding Salient Curves. 2006 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW'06). 2006; |
| Crandall, David, Felzenszwalb, Pedro, Huttenlocher, Daniel Object Recognition by Combining Appearance and Geometry. Automata, Languages and Programming. 2006; : 462-482. |
| Felzenszwalb, P.F. Representation and detection of deformable shapes. IEEE Transactions on Pattern Analysis and Machine Intelligence. 2005; 27 (2) : 208-220. |
| Crandall, D., Felzenszwalb, P., Huttenlocher, D. Spatial Priors for Part-Based Recognition Using Statistical Models. 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05). 2005; |
| Felzenszwalb, P.F., Huttenlocher, D.P. Efficient belief propagation for early vision. Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004.. 2004; |
P. Felzenszwalb, R. Zabih. Dynamic Programming and Graph Algorithms in Computer Vision. IEEE Transactions on Pattern Analysis and Machine Intelligence, Volume 33, Number 4, Pages 721-740, April 2011.
P. Felzenszwalb, D. McAllester. Object Detection Grammars. University of Chicago, Department of Computer Science, Technical Report 2010-02, February 2010.
P. Felzenszwalb, J. McAuley. Fast Inference with Min-Sum Matrix Product. University of Chicago, Department of Computer Science, Technical Report 2010-04, August 2010.
P. Felzenszwalb, R. Girshick, D. McAllester, D. Ramanan. Object Detection with Discriminatively Trained Part Based Models. IEEE Transactions on Pattern Analysis and Machine Intelligence, Volume 32, Number 9, Pages 1627-1645, September 2010.
L. Babai, P. Felzenszwalb. Computing Rank Convolutions with a Mask. ACM Transactions on Algorithms, Volume 6, Issue 1, Article 20, December 2009.
P. Felzenszwalb, D. McAllester. The Generalized A* Architecture. Journal of Artificial Intelligence Research, Volume 29, Pages 153-190, May 2007.
P. Felzenszwalb, D. Huttenlocher. Efficient Belief Propagation for Early Vision. International Journal of Computer Vision, Vol. 70, No. 1, Pages 41-54, October 2006.
P. Felzenszwalb, D. Huttenlocher. Pictorial Structures for Object Recognition. International Journal of Computer Vision, Vol. 61, No. 1, Pages 55-79, January 2005.
P. Felzenszwalb. Representation and Detection of Deformable Shapes. IEEE Transactions of Pattern Analysis and Machine Intelligence, Vol. 27, No. 2, Pages 208-220, February 2005.
P. Felzenszwalb, D. Huttenlocher. Efficient Graph-based Image Segmentation. International Journal of Computer Vision, Vol. 59, No. 2, Pages 167-181, September 2004.
P. Felzenszwalb. Representation and Detection of Shapes in Images. Ph.D. thesis. MIT Artificial Intelligence Laboratory, Technical Report 2003-016.
| Year | Degree | Institution |
|---|---|---|
| 2003 | PhD | Massachusetts Institute of Technology |
| 2001 | MS | Massachusetts Institute of Technology |
| 1999 | BS | Cornell University |
ACM Grace Murray Hopper Award
IEEE Technical Achievement Award
PASCAL Visual Object Challenge "Lifetime Achievement" Prize
Longuet-Higgins Prize
NSF Faculty Early Career Development (CAREER) Award
| CSCI 1420 - Introduction to Machine Learning |
| CSCI 1420 - Machine Learning |
| ENGN 1570 - Linear System Analysis |
| ENGN 1610 - Image Understanding |
| ENGN 2520 - Pattern Recognition and Machine Learning |
| ENGN 2912P - Topics in Optimization |
