Visual Analysis of High DOF Articulated Objects with Application to Hand
Tracking
J. M. Rehg,
Ph.D. Thesis, Carnegie Mellon University, Dept. of Electrical and Computer
Engineering, Technical Report CMU-CS-95-138, 1995
(pdf, 1.7 Mb)
Computer-Aided Synthesis of Routine Designs
J. M. Rehg,
M.S. Thesis, Carnegie Mellon University, Dept. of Electrical and Computer
Engineering, 1988.
Learning and Inferring Motion Patterns using Parametric Segmental
Switching Linear Dynamic Systems
S. Oh, J. M. Rehg, T. Balch, and F. Dellaert
Int. J. of Computer Vision, Special issue on Learning for Vision
Accepted for publication
On the Design of Cascades of Boosted Ensembles for Face Detection
S. C. Brubaker, J. Wu, J. Sun, M. D. Mullin, and J. M. Rehg
Int. J. of Computer Vision, Special Issue on Learning for Vision
Accepted for publication
Shadow Elimination and Blinding Light Suppression for Interactive
Projected Displays
J. Summet, M. Flagg, T.-J. Cham, J. M. Rehg, and R. Sukthankar
IEEE Transactions on Visualization and Computer Graphics
Accepted for publication
Learning from Examples in Unstructured Outdoor Environments
J. Sun, T. Mehta, D. Wooden, M. Powers, J. M. Rehg, T. Balch, and M.
Egerstedt
Journal of Field Robotics
Accepted for publication
A Data-Driven Approach to Quantifying Natural Human Motion
L. Ren, A. Patrick, A. Efros, J. Hodgins, and J. M. Rehg
ACM Transactions on Graphics, Special Issue: Proceedings of the 2005 SIGGRAPH
Conference, 24(3):1090-1097, August 2005.
(project page,
pdf 2Mb,
video 93Mb,
video 56Mb)
Experiences with Optimizing Two Stream-Based Applications for Cluster Execution
Y. Angelov, U. Ramachandran, K. Mackenzie, J. M. Rehg, and I. Essa
J. of Parallel and Distributed Computing, 65(6):678-691, June 2005.
Boosted Learning in Dynamic Bayesian Networks for Multimodal Speaker
Detection
V. Pavlovic, A. Garg, and J. M. Rehg,
Proceedings of the IEEE, 91(9):1355-1369, September 2003.
Stampede: A Cluster Programming Middleware for Interactive Stream-Oriented
Applications
U. Ramachandran, R. S. Nikhil, J. M. Rehg, Y. Angelov, A. Paul, S. Adhikari,
K. Mackenzie, N. Harel, and K. Knobe,
IEEE Transactions on Parallel and Distributed Systems, 14(11):1140-1154,
November 2003.
Ambiguities in Visual Tracking of Articulated Objects Using Two- and
Three-Dimensional Models
J. M. Rehg, D. D. Morris, and T. Kanade,
Int. J. of Robotics Research, 22(6):393-418, June 2003.
(pdf, 0.5 Mb galley proofs)
Statistical Color Models with Application to Skin Detection
M. J. Jones and J. M. Rehg,
Int. J. of Computer Vision, 46(1):81-96, Jan 2002.
(pdf, 0.48 Mb), (pdf,
5.1 Mb)
Integrated Task and Data Parallel Support for Dynamic Applications
J. M. Rehg, K. Knobe, U. Ramachandran, R. S. Nikhil, and A. Chauhan,
Scientific Programming, 7(3-4):289–302, 1999. Invited paper, selected
from 1998 Workshop on Languages, Compilers, and Run-Time Systems.
(pdf, 0.75 Mb)
A Bayesian Multiple Hypothesis Approach to Edge Grouping and Contour
Segmentation
I. J. Cox, J. M. Rehg, and S. Hingorami,
Int. J. of Computer Vision, 11(1):5-24, 1993.
Projector-Guided Painting
M. Flagg and J. M. Rehg
19th ACM Symposium on User Interface Software and Technology (UIST 06),
Montreux, Switzerland, October 2006.
(project
page,
pdf)
GVU-PROCAMS: Enabling Novel Projected Interfaces
J. Summet, M. Flagg, J. M. Rehg, and G. Abowd
ACM Multimedia, Santa Barbara, CA, October 2006. Accepted for
publication.
(project page)
Traversability Classification Using Unsupervised On-Line Visual Learning
for Outdoor Robot Navigation
D. Kim, J. Sun, S. M. Oh, J. M. Rehg, and A. Bobick
IEEE Intl. Conf. on Robotics and Automation (ICRA 06), Orlando, FL, May
2006.
(pdf,
slides)
Towards Optimal Training of Cascade Classifiers
S. C. Brubacker, M. D. Mullin, and J. M. Rehg
European Conference on Computer Vision (ECCV 06), Graz, Austria, May
2006.
(pdf)
Learning and Inference in Parametric Switching Linear Dynamic Systems
S. M. Oh, J. M. Rehg, T. Balch, and F. Dellaert
International Conference on Computer Vision (ICCV 05), Vol. 2, pages
1161-1168, Beijing, China, October 2005.
(project page,
pdf)
Data-Driven MCMC for Learning and Inference in Switching Linear Dynamic
Systems
S. M. Oh, J. M. Rehg, T. Balch, and F. Dellaert
Twentieth National Conference on Artificial Intelligence (AAAI 05),
Pittsburgh, PA, July 2005.
(project page,
pdf)
Linear Asymmetric Classifier for Face Detection
J. Wu, M. D. Mullin, and J. M. Rehg
International Conference on Machine Learning (ICML 05), pages 993-1000, Bonn, Germany,
August 2005.
(pdf)
Efficient Discriminative Learning of Bayesian Network Classifiers via
Boosted Augmented Naive Bayes
Y. Jing, V. Pavlovic, and J. M. Rehg
International Conference on Machine Learning (ICML 05), pages 369-376, Bonn, Germany,
August 2005.
Recipient of Distinguished Student Paper Award
(pdf)
Virtual Rear Projection: Do Shadows Matter?
J. Summet, G. Abowd, G. Corso, and J. M. Rehg
CHI '05 Extended Abstracts. 2005.
Using Sound Source Localization in a Home Environment
X. Bian, G. Abowd, J. M. Rehg
Third Intl. Conf. on Pervasive Computing (Pervasive 05). Munich, Germany, 2005.
A Flexible Projector-Camera System for Multi-Planar Displays
M. Ashdown, M. Flagg, R. Sukthankar, and J. M. Rehg
Computer Vision and Pattern Recognition (CVPR 04), pages II:165-172. Washington,
DC, June, 2004.
Automatic Cascade Training with Perturbation Bias
J. Sun, J. M. Rehg, and A. Bobick
Computer Vision and Pattern Recognition (CVPR 04), pages II:276-283. Washington,
DC, June, 2004.
(pdf, 0.13
Mb)
Asymmetrically Boosted HMM for Speech Reading
P. Yin, I. Essa, and J. M. Rehg
Computer Vision and Pattern Recognition (CVPR 04), pages II:755-761. Washington,
DC, June, 2004.
Active Learning for Automatic Classification of Software Behavior
J. Bowring, J. M. Rehg, and M. J. Harrold
To appear in Proc. Intl. Symposium on Software Testing and Analysis (ISSTA
2004), July 2004.
(abstract)
Learning a Rare Event Detection Cascade by Direct Feature Selection
J. Wu, J. M. Rehg, and M. D. Mullin.
Proc. Advances in Neural Information Processing Systems 16 (NIPS*2003), MIT
Press, 2004.
(pdf,
0.11 Mb), (software)
Shadow Elimination and Occluder Light Suppression for Multi-Projector
Displays
T.-J. Cham, J. M. Rehg, R. Sukthankar, and G. Sukthankar,
Computer Vision and Pattern Recognition (CVPR 03), pages 513-520, Madison, WI, June,
2003.
(pdf, 0.16 Mb)
Projected Light Displays Using Visual Feedback
J. M. Rehg, M. Flagg, T.-J. Cham, R. Sukthankar, and G. Sukthankar,
Intl. Conf. on Control, Automation, Robotics, and Vision,
Singapore, Dec. 2-5, 2002.
(pdf, 0.56 Mb)
Boosting and Structure Learning in Dynamic Bayesian Networks for
Audio-Visual Speaker Detection
T. Choudhury, J. M. Rehg, V. Pavlovic, and A. Pentland,
Intl. Conf. on Pattern Recognition, pages III:789-794, Quebec City,
Canada, August 11-15, 2002.
(pdf, 0.11 Mb)
Reconstruction of 3-D Figure Motion from 2-D Correspondences
D. DiFranco, T.-J. Cham, and J. M. Rehg,
Computer Vision and Pattern Recognition, Kauai, Hawaii, Dec. 2001.
(pdf, 0.67 Mb), (pdf
8.2 Mb)
Learning Switching Linear Models of Human Motion
V. Pavlovic, J. M. Rehg, and J. MacCormick,
Advances in Neural Information Processing Systems 13 (NIPS*2000), MIT
Press, 2001.
(pdf, 0.44 Mb)
Impact of Dynamic Model Learning on Classification of Human Motion
V. Pavlovic and J. M. Rehg,
Computer Vision and Pattern Recognition, volume 1, pages 788–795,
Hilton Head, SC, June 13-15 2000.
(pdf, 0.18 Mb)
Multimodal Speaker Detection Using Error Feedback Dynamic Bayesian
Networks
V. Pavlovic, A. Garg, J. M. Rehg, and T. S. Huang,
Computer Vision and Pattern Recognition, volume 2, pages 34-41, Hilton
Head Island, SC, June 13-15, 2000.
(pdf, 2.1 Mb)
Audio-Visual Speaker Detection Using Dynamic Bayesian Networks
A. Garg, V. Pavlovic, and J. M. Rehg
Fourth International Conference on Automatic Face and Gesture Recognition,
pages 384-390, Grenoble, France, March, 2000.
A Dynamic Bayesian Network Approach to Figure Tracking Using Learned
Dynamic Models
V. Pavlovic, J. M. Rehg, T.-J. Cham, and K. Murphy,
Intl. Conf. on Computer Vision, volume 1, pages 94–101, Kerkyra,
Greece, Sept. 20-27 1999.
(pdf, 0.56 Mb)
Dynamic Feature Ordering for Efficient Registration
T.-J. Cham and J. M. Rehg,
Intl. Conf. on Computer Vision, volume 2, pages 1084–1091, Kerkyra,
Greece, Sept. 20-27, 1999.
(pdf, 1.7 Mb)
A Multiple Hypothesis Approach to Figure Tracking
T.-J. Cham and J. M. Rehg,
Computer Vision and Pattern Recognition, volume 2, pages 239–245, Ft.
Collins, CO, June 1999.
(pdf, 0.5 Mb)
Vision-Based Speaker Detection Using Bayesian Networks
J. M. Rehg, K. P. Murphy, and P. W. Fieguth,
Computer Vision and Pattern Recognition, volume 2, pages 110-116, Ft. Collins, CO,
June, 1999.
(pdf, 0.64 Mb)
Statistical Color Models with Application to Skin Detection
M. Jones and J. M. Rehg
Computer Vision and Pattern Recognition, volume 1, pages 274-280, Ft. Collins, CO,
June, 1999.
Singularity Analysis for Articulated Object Tracking
D. D. Morris and J. M. Rehg,
Computer Vision and Pattern Recognition, pages 289–296, Santa Barbara,
CA, June 23-25, 1998.
(pdf, 0.16 Mb)
Vision for a Smart Kiosk
J. M. Rehg, M. Loughlin, and K. Waters,
Computer Vision and Pattern Recognition, pages 690–696, San Juan, Puerto
Rico, June 17-19, 1997.
(pdf, 0.24 Mb)
Analyzing Articulated Motion Using Expectation-Maximization
H. A. Rowley and J. M. Rehg
Computer Vision and Pattern Recognition, pages 935–941, San Juan, Puerto
Rico, June 17-19, 1997.
Model-Based Tracking of Self-Occluding Articulated Objects
J. M. Rehg and T. Kanade
Intl. Conf. on Computer Vision, pages 612-617, Cambridge, MA, June 20-23,
1995.
(pdf, 0.3 Mb)
Visual Tracking of High DOF Articulated Structures: An Application to
Human Hand Tracking
J. M. Rehg and T. Kanade
European Conference on Computer Vision, volume II, pages 35-46,
Stockholm, Sweden, 1994.
A Bayesian Multiple Hypothesis Approach to Contour Segmentation
I. J. Cox, J. M. Rehg, and S. Hingorami
European Conference on Computer Vision, pages 72-77, Santa Margherita
Ligure, Italy, 1992.
Visual Tracking with Deformation Models
J. M. Rehg and A. P. Witkin
International Conference on Robotics and Automation, pages 844–850,
Sacramento, CA, April 1991.
Improving the Speed of Virtual Rear Projection: A GPU-Centric Architecture
M. Flagg, J. Summet, and J. M. Rehg
Second IEEE International Workshop on Projector-Camera Systems (PROCAMS 05),
San Diego, CA, June, 2005.
Software Behavior: Automatic Classification and its Applications
J. F. Bowring, J. M. Rehg, and M. J. Harrold
Technical Report GIT-CERCS-03-19, Georgia Institute of Technology, Atlanta, GA,
October 2003.
(Abstract)
(pdf,
0.4 Mb)
Learning a Rare Event Detection Cascade by Direct Feature Selection
J. Wu, J. M. Rehg, and M. D. Mullin
Technical Report GIT-GVU-03-16, Georgia Institute of Technology, Atlanta, GA,
July 2003.
(Abstract) (pdf,
0.2 Mb)
Virtual Rear Projection: An Empirical Study of Shadow Elimination for
Large Upright Displays
J. Summet, G. D. Abowd, G. M. Corso, and J. M. Rehg
Technical Report GIT-GVU-03-13, Georgia Institute of Technology, Atlanta, GA,
May 2003.
(Abstract) (pdf,
0.2 Mb)
Shadow Elimination and Occluder Light Suppression for Multi-Projector
Displays
T.-J. Cham, R. Sukthankar, J. M. Rehg, and G. Sukthankar,
Technical Report CRL 2002/03, Compaq Computer Corporation, Cambridge Research
Laboratory, Cambridge, MA, March 2002.
(pdf, 0.23 Mb)
Singularities in Articulated Object Tracking with 2-D and 3-D Models
J. M. Rehg and D. D. Morris,
Technical Report CRL 97/8, Digital Equipment Corporation, Cambridge Research
Laboratory, Cambridge, MA, October 1997.
(pdf, 0.54 Mb)