Ray Rimey

Projects

This page provides some more detail about many of my research projects plus some pictures. Click on a picture for its full-size version.

Activity Understanding, LM, 2004-present.

This project is exploring new concepts for modeling, learning, recognizing and understanding activities observed by wide-area persistent surveillance sensors and by people.

Related Publications:

R.D. Rimey, et al., "Network Exploitation Using Wide Area Motion Imagery Tracks," Special Session on Wide Area Persistent Surveillance, Proceedings SPIE Defense, Security, and Sensing Symposium, To appear April 2011.
R.D. Rimey, "Recognizing Activity Structures in Massive Numbers of Simple Events Over Large Areas," In Distributed Video Sensor Networks, B. Bhanu, C. Ravishankar, A. Roy-Chowdhury, D. Terzopoulos, H. Aghajan, eds., Springer, To appear February 2011.
W.A. Hoff, J.W. Howard, "Activity Recognition in a Dense Sensor Network," Proceedings: First International Conference on Sensor Networks and Applications, 2009. PDF
R.D. Rimey, D. Keefe, "Temporal Structure Methods for Image-Based Change Analysis," Proceedings: 37^th Applied Imagery and Pattern Recognition Workshop, 2008. PDF
R.D. Rimey, D. Keefe, "Exploitation of Massive Numbers of Simple Events," Proceedings: 37^th Applied Imagery and Pattern Recognition Workshop, 2008.
R.D. Rimey, W. Hoff, J.Y. Lee, "Recognizing Wide-Area and Process-Type Activities," Proceedings: International Conference on Information Fusion, 2007. PDF
J.Y. Lee, W. Hoff, "Activity Identification Utilizing Data Mining Techniques," Proceedings: IEEE Workshop on Motion and Video Computing (WMVC), 2007. PDF
R.J. Parker, W.A. Hoff, A. Norton, J.Y. Lee, M.D. Colagrosso, "Activity Identification and Visualization," Proceedings: Fifth International Workshop on Pattern Recognition in Information Systems (PRIS), 2005, pages 124-133. PDF

Sketch Representations of Activity, LM, 2006-2008.

This project explored how sketchs and diagrams can be used to represent complex activity and how analysts might use sketch-based tools to reason about activity.

Related Publications:

J.F. Sullivan, M. Banasiak, C. Messick, R. Rimey, "Social-Technical Tools for Collaborative Sensemaking and Sketching," Proceedings: HCI International, 2009. PDF
R.D. Rimey, D. Keefe, "Exploitation of Massive Numbers of Simple Events," Proceedings: 37^th Applied Imagery and Pattern Recognition Workshop, 2008.

Zoomable User Interfaces (ZUIs) and Lens Tools, LM, 1997-2004.

Several projects explored how zoomable user interface (ZUI) and lens concepts can benefit future analysis tools. One project examined analysis tasks involving a large amount and variety of visual work materials, techniques for externalizing analysis tasks on a ZUI canvas, and the benefits of the resulting new analysis environment. These projects built on Professor Ben Bederson's Piccolo, Jazz and Pad++ toolkits for zoomable graphics. We developed lenses in numerous tools: Piccolo, Jazz, Pad++, OpenMap, JLoox, WebELT, Swing.

Related Publications:

R.D. Rimey, D.S. Bolme, "Re-Using Millions of Visualizations," Visualization and Data Analysis, Proceedings SPIE-IS&T Electronic Imaging, Volume 6495, 2007. Paper, Slides, Video #1, Video #2
R.D. Rimey, R. Withman, "Interactive Image Exploitation," Proceedings: National Fire Control Symposium, 1999. PDF
R.D. Rimey, W.N. Klarquist, and C.H. Debrunner, "Design of Zoomable User Interfaces and Lens Tools for Intelligence Analysis," 27^th AIPR Workshop: Advances in Computer-Assisted Recognition, Proceedings SPIE, Volume 3584, 1998, pages 17-28. PDF

Intelligent Mobile Sensor System (IMSS), LM, 1995-1997

The IMSS project developed a fully-autonomous indoor mobile robot system that drives around and inspects 55-gallon drums stored in warehouses. The project culminated with two month-long field tests inside warehouses containing drums of low-level radioactive and hazardous waste at the DOE's Fernald, OH and Idaho Falls, ID locations.

Related Publications:

DOE Fact Sheet on IMSS. PDF
E. Byler, W. Chun, W. Hoff, D. Layne, "Autonomous Hazardous-Waste Drum Inspection Vehicle," Robotics and Automation Magazine, 2(1):6-17, March 1995. PDF
E.A. Byler, "Navigation, Behaviors, and Control Modes in an Autonomous Vehicle," Mobile Robots IX, Proceedings SPIE, Volume 2352, 1995, pages 106-115. PDF

Unmanned Ground Vehicle / Demo II, LM, 1993-1997

The UGV / Demo II program, begun in 1992, developed and matured those navigation and automatic target recognition technologies critical for the development of supervised, autonomous ground vehicles capable of performing military scout missions with a minimum of human over-sight. The program culminated with a highly successful series of field exercises performed by soldiers at Ft. Hood, Texas over three weeks in May-June 1996.

Related Publications:

In Reconnaissance, Surveillance, and Target Acquisition for the Unmanned Ground Vehicle: Providing Surveillance 'Eyes' for an Autonomous Vehicle, O. Firschein, T.M. Strat, eds., Morgan Kaufman, 1997:

J.R. Spofford, R.D. Rimey, S.H. Munkeby, "Overview of the UGV / Demo II Program," pages 21-40. PDF
J.R. Spofford, R.D. Rimey, "Description of the UGV / Demo II System," pages 41-50. PDF Also in Proceedings: Association for Unmanned Vehicle Systems International Conference, 1997, pages 255-264.
J.R. Spofford, S.H. Munkeby, R.D. Rimey, "The Annual Demonstrations of the UGV / Demo II Program," pages 51-91. PDF
D.R. Hougen, R.D. Rimey, W.E. Severson, "Description of the RSTA Subsystem," pages 145-155. PDF
R.D. Rimey, S.J. Hennessy, D.R. Hougen, "Experiences Building the Integrated RSTA System," pages 157-169. PDF

S.H. Munkeby, R.D. Rimey, J.R. Spofford, "Unmanned Ground Vehicle / Combat Asset Deployment and Retrieval," Proceedings: Conference on Technology Assessment for Unmanned Ground Vehicles, IDA Document D-1817, 1995, pages 505-520. PDF
W.E. Severson, R.D. Rimey, "Reconnaissance, Surveillance, and Target Acquisition in the UGV / Demo II Program," Proceedings: Fourth ATR Systems and Technology Symposium, Volume I - Unclassified, 1994, pages 129-142. PDF

Control of Selective Perception (PhD thesis), Department of Computer Science, University of Rochester, 1990-1993

My PhD thesis developed methods for selecting a sequence of camera viewpoints and selecting algorithms to process the acquired images in order to answer a question about a scene. My advisor was Professor Chris Brown.

Related Publications:

R.D. Rimey, C.M. Brown, "Control of Selective Perception Using Bayes Nets and Decision Theory," International Journal of Computer Vision, 12(2/3):173-207, 1994. PDF
R.D. Rimey, "Control of Selective Perception Using Bayes Nets and Decision Theory," University of Rochester, Department of Computer Science, Ph.D. Thesis, 1993. Available as Technical Report 468, December 1993. PDF
R.D. Rimey, "Studying Control of Selective Perception Using T-world and TEA," Proceedings: IEEE Workshop on Qualitative Vision, 1993, pages 51-60. PDF Similar paper in Proceedings: DARPA Image Understanding Workshop, 1993, pages 575-580.
P.A. von Kaenel, C.M. Brown, R.D. Rimey, "Goal-Oriented Dynamic Vision," University of Rochester, Department of Computer Science, Technical Report 466, August 1993. PDF
R.D. Rimey, "Where to Look Next Using a Bayes Net: An Overview," Proceedings: DARPA Image Understanding Workshop, 1992, pages 927-932. PDF
R.D. Rimey, "Where to Look Next Using a Bayes Net: The TEA-1 System and Future Directions," Working Notes: AAAI Spring Symposium Series, Workshop on Control of Selective Perception, 1992, pages 118-122. PDF
R.D. Rimey, C.M. Brown, "Task-Specific Utilities in a General Bayes Net Vision System," Proceedings: IEEE Conference on Computer Vision and Pattern Recognition, 1992, pages 142-147. PDF
R.D. Rimey, C.M. Brown, "Task-Oriented Vision With Multiple Bayes Nets," Active Vision, A. Blake, A. Yuille, eds., MIT Press, 1992, pages 217-236.
R.D. Rimey, C.M. Brown, "Where to Look Next Using a Bayes Net: Incorporating Geometric Relations," Proceedings: European Conference on Computer Vision, 1992, pages 542-550. PDF
R.D. Rimey, C.M. Brown, "Where to Look Next Using a Bayes Net: Incorporating Geometric Relations," Video Proceedings: European Conference on Computer Vision, 1992, 2 minutes.

Applications of Hidden Markov Models to Computer Vision, Department of Computer Science, University of Rochester, 1988-1989

This project examined the use of hidden Markov models for some computer vision problems, including using them to drive the motion sequences of a camera.

Related Publications:

R.D. Rimey, C.M. Brown, "Controlling Eye Movements With Hidden Markov Models," International Journal of Computer Vision, 7(1):47-65, 1991. PDF
R.D. Rimey, C.M. Brown, "Sequences, Structure, and Active Vision," Proceedings: IEEE Conference on Computer Vision and Pattern Recognition, 1991, pages 706-707. PDF
R.D. Rimey, C.M. Brown, "Selective Attention as Sequential Behavior: Modeling Eye Movements With an Augmented Hidden Markov Model," Proceedings: DARPA Image Understanding Workshop, 1990, pages 840-849. PDF

Applications of Neural Networks to Computer Vision, Nestor Inc., 1985-1988

I developed the performance evaluation subsystem of the Nestor Development System product (NDS-1000), a developer toolkit for solving pattern classification problems. I also created demo applications of the NDS to three computer vision applications. Nestor existed from 1983 to 2009, and developed products for character recognition, fraud detection, and red-light camera systems.

Related Publications:

D.L. Reilly, C. Scofield, P.R. Gouin, R. Rimey, E.A. Collins, S. Ghosh, "An Application of a Multiple Neural Network Learning System to Industrial Part Inspection," Proceedings: ISA/88 (Instrument Society of America) International Conference and Exhibit, 1988, pages 1679-1690. PDF
R. Rimey, P. Gouin, C. Scofield, D.L. Reilly, "Real-Time 3-D Object Classification Using a Learning System," Intelligent Robots and Computer Vision V, Proceedings SPIE, Volume 726, 1986, pages 552-557. PDF

Recognizing Models in Range Data (MS thesis), Department of Electrical Engineering, University of Rhode Island, 1983-1985

I developed a maximum likelihood approach to segmenting 3D range data and matching 3D object models. My advisor was Professor Fernand Cohen, who is now at Drexel University. I also built the low-level software to enable acquisition and manipulation of raw range data from a sensor built by another student.

Related Publications:

R. Rimey, F. Cohen, "A Maximum-Likelihood Approach to Segmenting Range Data," IEEE Journal of Robotics and Automation, 4(3):277-286, 1988. Also in Proceedings: IEEE Conference on Robotics and Automation, 1988, pages 1696-1701. PDF
F.S. Cohen, R.D. Rimey, J.P. Cayula, "Segmentation of Three Dimensional Range Data," Proceedings: IEEE International Conference on Acoustics, Speech, and Signal Processing, 1985, pages 925-928. PDF
F.S. Cohen, R.D. Rimey, J. Cayula, "Real-Time 3-D Object Recognition from a Range or Visible Light Image," Computer Vision for Robots, Proceedings SPIE, Volume 595, 1985, pages 2-11. PDF
R.D. Rimey, "Recognition and Location Estimation of 3-D Objects in Range Data," University of Rhode Island, Department of Electrical Engineering, M.S. Thesis, 1985.
R. Rimey, I. Urbach, R. Kelley, "The URI Laser Range Finder: Hardware Upgrade and Software Support," University of Rhode Island, Robotics Research Center, Technical Report 39, June 1984.

Extracting Wireframe Building Models from Aerial Images, Department of Electrical and Computer Engineering, Carnegie Mellon University, 1982-1983

This was an undergraduate project during my senior year and the summer before. I developed a system that hypothesized matches of a flat-roofed N-sided building model to a line/junction segmentation of an aerial image of an urban area, and used a straight-line Hough transform to find additional predicted, but weaker, building edges in the original image data. My project sponsor was Professor Takeo Kanade.

Related Publications:

R. Rimey, "A Model-based Search to Find Buildings in an Aerial Image," Carnegie Mellon University, Senior Undergraduate Project, Final Report, May 1983. PDF