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ABOUT DR. KEITH HANNA

Dr. Hanna was awarded a multi-disciplinary Engineering Sciences degree from Oxford University majoring in Electrical Engineering. Dr. Hanna then spent 3 years at the Medical Engineering Unit and the Robotics Research Group also at Oxford University working towards the D.Phil degree in Medical Imaging and Computer Vision, including 2 years working with clinicians at the Nuffield Laboratory of Ophthalmology developing algorithms to test the efficacy of anti-cataract drugs. His D.Phil advisors, Professor Sir Michael Brady and Dr. Lionel Tarassenko, are pioneers in biomedical signal processing, and computer vision and medical imaging.

Dr. Hanna then held several positions at Sarnoff SRI in Princeton over 15 years, including Head, Vision Systems, working in the commercial and government domains developing and deploying pioneering algorithms, software, and systems for transformative real-world applications such as autonomous vehicle navigation, virtual reality systems, video surveillance, and biometrics.

Dr. Hanna then co-founded EyeLock, a major biometric company, where he held the position of CTO for over 10 years, developing and deploying advanced biometric hardware and software solutions for commercial and consumer applications.

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Dr. Hanna has spent more than 13 years throughout his career embedded in commercial startup or spin-off companies to transition development from the research environment to the deployed environment. Deployments include: video traffic detection systems now deployed at roadsides worldwide to optimize traffic flow, systems deployed across continents for processing video from unmanned aerial vehicles/drones, biometric iris-access ATMs, the first iris-biometric-access skyscraper at the headquarters of a major financial institution in the US, and the Emmy-award-winning vision system now deployed globally for embedding graphics within televised sports events including the yellow first-down-line in American football. He also developed the pioneering 3D Tactical Video Capture Systems technology (TVCS), performed initial deployments, and managed its transition to a major defense contractor resulting in deployments worldwide.

In 2017 Dr. Hanna founded and became CEO of IPRD Solutions, with the mission of applying his extensive research, development and deployment experience in both startup and established commercial and Governmental environments, to provide access to disruptive and impactful advanced scalable digital health innovations in lower-to-middle income countries.

Dr. Hanna has over 25 publications and is an inventor on over 100 patents. He was awarded the 2007 Most Influential Paper over the Decade Award from the International Association of Pattern Recognition.

PUBLICATIONS AND PATENTS

LARGE LANGUAGE MODELS

  • J. Doshi, K. Jois, A. Kumar, K. Hanna and P. Anandan. With acknowledgements to: B. Gupta and M. Shanbhag, S. Blagsvedt, R. Gandhi, P. Small, CK Cheruvettolil; Bill and Melinda Gates Foundation â€‹The LLM Landscape for LMICs: Overview, Evaluation Framework, Evaluation Components, Initial Recommendations" 2023

AUTONOMOUS NAVIGATION AND MAPPING FOR ADAS AND DRONES

  • Gelbart, S. Driscoll, J. Freeman, G. J. Fetzer, D. Wasson, K. Hanna, W. Yi Zhao, “Signal processing, image registration, and visualization of FLASH lidar data” Laser Radar Technology and Applications VIII, G. W. Kammerman, Editor, Proc. SPIE Vol. 5086, 197-208, 2003.

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  • R. Kumar, H. Sawhney, S. Samarasekera, S. Hsu, H. Tao, Y. Guo, K. Hanna, A. Pose, R. Wildes, D. Hirvonen, M. Hansen, P. Burt, "Aerial Video Surveillance and Exploitation,"   Proceedings of the IEEE, Special Issue on Third Generation Surveillance Systems, 89(10):1518-1539, Oct. 2001.
     

  • R. Kumar, S. Samarasekera, S. Hsu, K. Hanna, "Registration of Highly-Oblique and Zoomed In Aerial Video to Reference Imagery." ICPR 00, Barcelona, Sept. 2000.
     

  • L. Wixson, K. Hanna, D. Mishra, Improved Illumination Assessment for Vision-Based Traffic Monitoring Proceedings of the 1998 IEEE Workshop on Visual Surveillance. January 1998.
     

  • R. Kumar, P. Anandan, and K.J. Hanna, "Direct recovery of shape from multiple views: a parallax based approach," Proceedings of the 12th IAPR International Conference on Pattern Recognition, vol. 1, pp. 685--688, 1994.
     

  • P. Burt, P. Anandan, K. Hanna, G. van der Wal, and R. Bassman, “A front-end vision processor for vehicle navigation.” In IAS-3, pages 653--662, Pittsburgh, PA, 1993.
     

  • K. J. Hanna and Neil E. Okamoto, "Combining stereo and motion analysis for direct estimation of scene structure," In Proc. Intl. Conf. on Computer Vision, pages 357-265, 1993.
     

  • Burt, Peter J.; Anandan, P.; Hanna, Keith, “Electronic front-end processor for active vision” (David Sarnoff Research Ctr.).  Proc. SPIE Vol. 1825, p. 769-780, Intelligent Robots and Computer Vision XI: Algorithms, Techniques, and Active Vision, David P. Casasent; Ed.  11/1992.  SPIE.
     

  • J.R. Bergen, P. Anandan, K. Hanna, R. Hingorani, "Hierarchical model-based motion estimation," In Proc. 2nd European Conference on Computer Vision, pages 237-252, 1992.
     

  • K. J. Hanna, "Direct Multi-resolution estimation of ego-motion and structure from motion"  In Proc. IEEE Workshop. on Visual Motion, Pages 156-162, 1991.
     

  • ​J.R. Bergen, P.J. Burt, K. Hanna, R. Hingoram, P. Jeanne, and S. Peleg, ”Dynamic multiple-motion computation” In Y.A. Feldman and A. Bruckstein, editors, Artificial Intelligence and Computer Vision: Proceedings of the Israeli Conference, pages 147 156. Elsevier, 1991.
     

  • US 7,363,157:  Method and apparatus for performing wide area terrain mapping
     

  • US 7,313,252:  Method and system for improving video metadata through the use of frame-to-frame correspondences
     

  • US 7,259,778:  Method and apparatus for placing sensors using 3D models
     

  • US 6,597,818:  Method and apparatus for performing geo-spatial registration of imagery 
     

  • US 6,571,024:  Method and apparatus for multi-view three dimensional estimation
     

  • US 5,629,988:  System and method for electronic image stabilization
     

  • US 5,259,040:  Method for determining sensor motion and scene structure and image processing system thereof

MULTI-MEDIA FOR SURVEILLANCE, BROADCAST TELEVISION, AND ADAS

  • H.S. Sawhney, A. Arpa, R. Kumar, S. Samarasekera, M. Aggarwal, S. Hsu, D. Nister, K. Hanna. "Video Flashlights -- Real Time Rendering of Multiple Videos for Immersive Model Visualization," Proc. Eurographics Workshop on Rendering, June 2002.
     

  • Keith J. Hanna, Harpreet S. Sawhney, Rakesh Kumar, Yanlin Guo, Supun Samarasekera: Annotation of Video by Alignment to Reference Imagery. ICMCS, Vol. 1 1999: 38-43
     

  • J. Asmuth, D. Dixon, K. Hanna, S. C. Hsu, R. Kumar, V. Paragano, A. Pope, S. Samarasekera, H. Sawhney, ”Multimedia Applications of Computer Vision” October, 1998 Proceedings of the 4th IEEE Workshop on Applications of Computer Vision (WACV’98)
     

  • R. Kumar, P. Anandan, J. Bergen, M. Irani and K.Hanna, “Representation of Scenes as a Collection of Images”, Proceedings IEEE Workshop on Visual Representation of Scenes, Cambridge, MA, May 1995.
     

  • P.J. Burt, K.J. Hanna, R.J. Kolczynski, “Enhanced Image Capture Through Fusion”, In Proceedings of the Workshop on Augmented Visual Display Research, pages 207–224. NASA – Ames Research Center., Dec. 1993.
     

  • US 7,929,017: Method and apparatus for stereo, multi-camera tracking and RF and video track fusion
     

  • US 7,260,274: Techniques and systems for developing high-resolution imagery
     

  • US 7,242,460: Method and apparatus for automatic registration and visualization of occluded targets using ladar data
     

  • US 7,085,409: Method and apparatus for synthesizing new video and/or still imagery from a collection of real video and/or still imagery
     

  • US 7,020,351: Method and apparatus for enhancing and indexing video and audio signals
     

  • US 6,907,073: Tweening-based codec for scaleable encoders and decoders with varying motion computation capability
     

  • US 6,522,787: Method and system for rendering and combining images to form a synthesized view of a scene containing image information from a second image
     

  • US 6,490,364: Apparatus for enhancing images using flow estimation
     

  • US 6,430,304: Method and apparatus for processing images to compute image flow information
     

  • US 6,269,175: Method and apparatus for enhancing regions of aligned images using flow estimation
     

  • US 5,963,664: Method and system for image combination using a parallax-based technique
     

  • US 5,923,791: Video merging employing pattern-key insertion
     

  • ​US 5,581,629: Method for estimating the location of an image target region from tracked multiple image landmark regions
     

  • US 5,566,251: Video merging employing pattern-key insertion
     

  • US 5,488,675: Stabilizing estimate of location of target region inferred from tracked multiple landmark regions of a video image

BIOMETRICS

  • J.R. Matey, O.Naroditsky, K.Hanna, R.Kolczynski, D.J.LoIacono, S.Mangru, M.Tinker, T.M.Zappia, W.Y.Zhao, “Iris on the Move: Acquisition of Images for Iris Recognition in Less Constrained Environments”, in Proc IEEE Col. 94(11), 2006, pp 1936-1947
     

  • Craig L. Fancourt, Luca Bogoni, Keith J. Hanna, Yanlin Guo, Richard P. Wildes, Naomi Takahashi, Uday Jain, “Iris Recognition at a Distance”, 5th International Conference AVBPA 2005, Hilton Rye Town, NY, USA, July 20-22, 2005, Proceedings. Lecture Notes in Computer Science 3546 Springer 2005, ISBN 3-540-27887-7
     

  • ​K. Hanna, R. Mandelbaum, D. Mishra, V. Paragano, L. Wixson, "A System for Non-Intrusive Human Iris Acquisition and Identification",  Proceedings of the International Association for Pattern Recognition Workshop on Machine Vision Applications, Tokyo, November 1996.
     

  • US 9,355,299: Fraud resistant biometric financial transaction system and method
     

  • ​US 9,311,536: Systems and methods for capturing artifact free images
     

  • ​US 9,280,706: Efficient method and system for the acquisition of scene imagery and iris imagery using a single sensor
     

  • ​US 9,192,297: System and method for iris data acquisition for biometric identification
     

  • US 9,142,070: Ensuring the provenance of passengers at a transportation facility
     

  • US 9,124,798: Systems and methods for illuminating an iris with visible light for biometric acquisition
     

  • ​US 9,122,925: Systems and methods for capturing artifact free images
     

  • ​US 9,117,119: Mobile Identity Platform
     

  • US 9,095,287: System and method for iris data acquisition for biometric identification
     

  • ​US 9,055,198: Mirror system and method for acquiring biometric data
     

  • US 9,036,871: Mobility identity platform
     

  • ​US 9,002,073: Mobile identity platform
     

  • ​US 8,965,064: Systems and methods for capturing artifact free images
     

  • US 8,965,063: Compact biometric acquisition system and method
     

  • ​US 8,958,606: Mirror system and method for acquiring biometric data
     

  • ​US 8,953,849: Method and system for biometric recognition
     

  • US 8,818,053: Methods for performing biometric recognition of a human eye and corroboration of same
     

  • US 8,818,052: Fraud resistant biometric financial transaction system and method
     

  • ​US 8,818,051: Fraud resistant biometric financial transaction system and method
     

  • ​US 8,798,334: Methods for performing biometric recognition of a human eye and corroboration of same
     

  • US 8,798,333: Methods for performing biometric recognition of a human eye and corroboration of same
     

  • ​US 8,798,331: Methods for performing biometric recognition of a human eye and corroboration of same
     

  • ​US 8,798,330: Methods for performing biometric recognition of a human eye and corroboration of same
     

  • ​US 8,604,901: Ensuring the provenance of passengers at a transportation facility
     

  • ​US 8,553,948: System and method for iris data acquisition for biometric identification
     

  • ​US 8,364,646: Scalable searching of biometric databases using dynamic selection of data subsets
     

  • ​US 8,306,279: Operator interface for face and iris recognition devices
     

  • ​US 8,280,120: Fraud resistant biometric financial transaction system and method
     

  • ​US 8,260,008: Methods for performing biometric recognition of a human eye and corroboration of same
     

  • ​US 8,212,870: Mirror system and method for acquiring biometric data
     

  • ​US 8,195,044: Biometric camera mount system
     

  • US 7,801,335: Apparatus and methods for detecting the presence of a human eye
     

  • ​US 6,714,665: Fully automated iris recognition system utilizing wide and narrow fields of view
     

  • ​US 6,088,470: Method and apparatus for removal of bright or dark spots by the fusion of multiple images
     

  • US 6,055,322: Method and apparatus for illuminating and imaging eyes through eyeglasses using multiple sources of illumination
     

  • ​US 5,751,836: Automated, non-invasive iris recognition system and method
     

  • US 5,572,596: Automated, non-invasive iris recognition system and method​

VIDEO SURVEILLANCE

  • Glen Francisco, Jennifer Tillman, Keith Hanna, Jeff Heubusch, Robert Ayers, “Integrated homeland security system with passive thermal imaging and advanced video analytics”, Proc. SPIE 6542, Infrared Technology and Applications XXXIII, 8th June 2007
     

  • Glen Francisco, Keith Hanna, Jeff Heubusch, Sharon Roberts, “Critical Infrastructure Security Confidence through Automated Thermal Imaging”, Proc. SPIE Defense and Security Symposium, 17-21 April 2006, Orlando, FL, USA
     

  • Wen-yi Zhao, Keith Hanna, Dave Schreder, “The application of computer vision to shipboard damage control”, ASNE Reconfiguration and Survivability Symposium 2005, Center for Advanced Power Systems, Florida State University, Tallahassee, FL
     

  • R. Kumar, H. Sawhney, S. Samarasekera, S. Hsu, H. Tao, Y. Guo, K. Hanna, A. Pose, R. Wildes, D. Hirvonen, M. Hansen, P. Burt, "Aerial Video Surveillance and Exploitation," Proceedings of the IEEE, Special Issue on Third Generation Surveillance Systems, 89(10):1518-1539, Oct. 2001.
     

  • US 8,289,390: Method and apparatus for total situational awareness and monitoring
     

  • ​US 8,063,936: Modular immersive surveillance processing system and method
     

  • ​US 7,949,295: Automated trainee monitoring and performance evaluation system
     

  • US 7,639,840: Method and apparatus for improved video surveillance through classification of detected objects
     

  • US 7,633,520: Method and apparatus for providing a scalable multi-camera distributed video processing and visualization surveillance system
     

  • ​US 7,522,186: Method and apparatus for providing immersive surveillance
     

  • ​US 7,385,626: Method and system for performing surveillance
     

  • US 7,382,898: Method and apparatus for detecting left objects
     

  • US 6,681,058: Method and apparatus for estimating feature values in a region of a sequence of images​

MEDICAL IMAGING

  • R. Kumar, J. C. Asmuth, K. J. Hanna, J. R. Bergen, D. B. Kopans, C. Hulka, R. H. Moore, "Application of 3D Registration for Detecting Lesions in Magnetic Resonance Breast Scans,"  SPIE-Medical Imaging, Newport Beach, CA, 1996.
     

  • Harris ML, Hanna KJ, Shun-Shin GA, Holden R, Brown NA.  Eye. 1993;7 ( Pt 4):572-7.  Analysis of retro-illumination photographs for use in longitudinal studies of cataract. 
     

  • Simpson A. J., Lee S., Hanna K. J. and Bron A. J. (1990). A method for measuring neuroretinal rim area. Australian And New Zealand Journal Of Ophthalmology. 18, 207-210.
     

  • Keith J. Hanna, L. Tarassenko: Tracking cataract by the four-line method. Image Vision Comput. 7(1): 57-62 (1989)

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