Christopher F. Barnes is an associate professor in the School of Electrical and Computer Engineering (ECE) at the Georgia Institute of Technology.
Dr. Barnes received his Ph.D. degree from Brigham Young University in 1989, after which he joined the Georgia Tech Research Institute (GTRI) as research faculty. He transferred to the School of ECE as an associate professor in 2002, and retains GTRI adjunct status as a principal research engineer.
Dr. Barnes has 27 years of experience in basic and applied research and has published approximately 140 papers and holds one patent.
He is recognized internationally for his expertise in synthetic aperture radar (SAR) analysis and SAR image formation processing. Dr. Barnes has twenty years of experience teaching SAR at the professional education and graduate student level. He has invented radar imaging image formation processing methods capable of three-dimensional coherently fused SAR imaging in remote sensing applications. This advanced radar signal processing method has applications in sonar, medical imaging and seismology. He has provided subject matter expertise in many research and development oversight activities of ground based and ship based radar signal processing and radar software engineering programs. Dr. Barnes is an expert in hardware/software architectures, software engineering, middleware, and object oriented/behavior decompositions for both functional and non-functional attributes of software intensive radar systems. He is also an expert in object-oriented software engineering tools, UML, C++, C and scripted languages, and software processes metrics.
Dr. Barnes' areas of basic research include image and video driven data mining and data compression. He has developed image driven data mining methods and systems that have proven capability in remotely sensed image processing for hurricane damage assessments. Dr. Barnes is supervising research in developing video driven data mining for video tracking. These video and image driven data mining systems are also being explored as possible foundations for new Internet search capabilities that correlate Internet images and videos based on image/video content similarity/dissimilarity. He is also applying data driven data mining systems to tasks such as computer assisted diagnosis of mammography and in various bioinformatic applications.
- Image Enabled and Video Enabled Data Mining
- Image and Video Data Compression
- Computing for Ground and Ship Based Radars
- Synthetic Aperture Radar Signal Processing
- Machine Vision
- Georgia Tech Outstanding Professional Education Award, 2009.
- Interdisciplinary Research Initiative Award, Georgia Tech Savannah, 2006.
- Certificate of Appreciation, Ground-Based Midcourse Defense Joint Program Office, Ballistic Missile Defense Organization, Department of Defense, 2002.
- Who's Who in Science and Engineering, 1998.
- Phi Kappa Phi, 1989, Sigma Xi, 1988. Eta Kappa Nu, 1986, and Phi Eta Sigma, 1983
Khan, I. A., Anderson D. V. and Barnes, C. F., "Classification using residual vector quantization with a Markov-Bayesian structure," ICASSP, 4-9 May 2014, Florence, Italy.
(Keynote Speaker) Barnes, C. F., "Synthetic Aperture Radar: Past, Present and Future," XV Defense Operational Applications Symposium (XV SIGE), Technological Institute of Aeronautics (ITA), Sao Jose dos Campos, Brazil, 25-27 September 2013.
Khan, I. A. and Barnes, C. F., "Fine-Grain Feature Attribution for Image Understanding Using Residual Vector Quantization," IGARSS 2012.
Khan, I. A. and Barnes, C. F., "Object Recognition from Residual Vector Quantization Generated Fine-Grained Segmentation Maps," ASPRS, pages 12-19, Milwaukee, Wisconsin, May 1-5, 2011.
Khan, I. A. and Barnes, C. F., "Using residual vector quantization for image content classification," ICASSP, 22-27 May 2011, pages 1041-1044, Prague, Czech Republic.
Yoo, J., Fritz, H. M., Haas, K. A., Work, P. A. and Barnes, C. F., "Depth inversion in the surf zone with inclusion of wave nonlinearity using video-derived celerity," ASCE's Journal of Waterway, Port, Coastal and Ocean Engineering, volume 137, number 2, pages 95-106, March/April 2011.
Burki, J. and Barnes, C.F, "Slant plane CSAR processing using Householder transform," IEEE Transactions on Image Processing, volume 17, number 10, pages 1900-1907, October 2008.
Barnes, C.F., "Image driven data mining for image content segmentation, classification and attribution," IEEE Transactions on Geoscience and Remote Sensing, volume 45, number 9, pages 2964-2978, September 2007.
Barnes, C.F., Fritz, H., and Yoo, J., "Hurricane disaster assessments with image driven data mining in high resolution satellite imagery," IEEE Transactions on Geoscience and Remote Sensing: Special Issue on Remote Sensing for Major Disaster Prevention, Monitoring and Assessment, part 1 of 2, volume 45, number 6, pages 1631-1640, June 2007.
Barnes, C.F. and Burki, J., "Late-season rural land-cover estimation with polarmetric-SAR intensity pixel blocks and sigma-tree structured near neighbor classifiers," IEEE Transactions on Geoscience and Remote Sensing, volume 44, number 9, pages 2384-2392, September 2006.
Last revised May 3, 2016