Department of Electrical, Computer, & Systems Engineering
Ph.D., Princeton University, Electrical Engineering
M.A., Princeton University, Electrical Engineering
M.A., Rice University, Computational and Applied Mathematics
B.A., Rice University, Mathematics, Computational and Applied Mathematics (dual)
- Distributed, active processing on hundred-camera networks
- 3D Modeling and tracking from distributed mobile sensors
- Computer vision, machine learning, and optimization for intensity-modulated radiotherapy
- Change detection and understanding in image and video sequences
- Magnetic field mapping via heavy ion beam spectral imaging
- I am interested in computer vision problems that occur in networks
of a large number (tens to hundreds) of cameras dispersed
throughout an environment. We have developed distributed solutions
for determining visual overlap and camera calibration in large
dynamic camera networks, which provide the basis for higher-level
vision problems (e.g. change detection, multi-object tracking,
image-based query, or view synthesis).
- I also collaborate on research involving 3D data representation,
registration, and integration of range and visual imagery. I am
particularly interested in change detection in range imagery and
joint fusion of EO/LiDAR data.
- I am also particularly interested in computer vision and machine
learning problems related to intensity modulated radiotherapy
(IMRT), an exciting new technology for cancer treatment. One
project involves developing computer vision algorithms to aid in
the automatic segmentation of organs from 3-D CT scans acquired
immediately prior to radiation treatment. A second project
investigates the relationship between a patient's body/organ
geometry and the multiple radiation beams that are used to treat
their cancer. We have investigated both the breast and prostate.
These projects include collaborations with medical physicists at
Memorial Sloan-Kettering Cancer Center and Massachusetts General
- A. Cheriyadat and R.J. Radke, Automatically Determining Dominant Motions
in Crowded Scenes by Clustering Partial Feature Trajectories. Proceedings
of the First ACM/IEEE International Conference on Distributed Smart
Cameras (ICDSC-07), September 2007.
- Y. Jeong and R.J. Radke, Reslicing Axially-Sampled 3D Shapes Using
Elliptic Fourier Descriptors. Elsevier Medical Image Analysis, Vol. 11,
No. 2, pp. 197-206, April 2007.
- R. Lu, R.J. Radke, L. Happersett, C.-S. Chui, J. Xiong, E. Yorke, and A.
Jackson, Reduced-Order Optimization for Simplifying Prostate IMRT
Planning, Physics in Medicine and Biology, Vol. 52, No. 3, pp. 849-870,
February 7, 2007.
- Dhanya Devarajan and Richard J. Radke, Calibrating Distributed Camera
Networks Using Belief Propagation. EURASIP Journal on Advances in Signal
Processing: Special Issue on Visual Sensor Networks, Volume 2007, Article
- Zhaolin Cheng, Dhanya Devarajan, and Richard J. Radke, Determining Vision
Graphs for Distributed Camera Networks Using Feature Digests. EURASIP
Journal on Advances in Signal Processing: Special Issue on Visual Sensor
Networks, Volume 2007, Article ID 57034.
Honors and Awards:
- Career Award, National Science Foundation, 2003
- Member, 2007 DARPA Computer Science Study Panel (12 PIs
- Elevated to Senior Member of the IEEE, August 2006.
- Senior Member of the IEEE, August 2006.
- Area Chair, IEEE Computer Vision and Pattern Recognition 2008
- Program Committee, International Conference on Distributed Smart Cameras
(ICDSC) 2007, IEEE Pacific-Rim Symposium on Image and Video
Technology (PSIVT '06), IEEE Computer Vision and Pattern Recognition
(CVPR) 2005-2007, European Conference on Computer Vision (ECCV) 2006,
IEEE International Conference on Computer Vision (ICCV) 2005, 2007,
Workshop on Omnidirectional Vision, Camera Networks, and Non-Classical
Cameras (OMNIVIS) 2005.
Jonsson Engineering Center Room 7006
Rensselaer Polytechnic Institute
110 8th Street
Troy, N.Y. 12180 USA
Phone: (518) 276-6483
Fax: (518) 276-8715