Matthew Dawkins is a staff R&D engineer on Kitware’s Computer Vision (CV) Team located in Clifton Park, New York. He specializes in object detection, object tracking, video search, image registration, multi-modal/stereo processing, and 3D modeling. He serves as project lead and senior developer on a variety of CV projects, which have collectively been worth millions of dollars.
Matt currently heads the development of Kitware’s Video and Image Analytics for Marine Environments (VIAME) platform. Originally funded by the National Oceanic and Atmospheric Administration (NOAA), VIAME has multiple ongoing projects relating to wildlife detection (e.g. scallops, fish, marine mammals) in multiple locations around the world.
Additionally, Matt has managed several projects funded by the U.S. Department of Defense (DoD), centered around object tracking and video search. In both NOAA, DoD, and commercial spaces, Matt led the writing of multiple accepted grant proposals including Small Business Innovation Research (SBIR) Phase I and Phase IIs, Air Force Research Laboratory (AFRL) proposals, and NOAA and industry support contracts.
Prior to joining Kitware, Matt was an intern at Biodex Medical Systems, Columbia University, and Boeing where he worked on an assortment of engineering and computer science problems.
Matt received his master’s degree in computer science from Rensselaer Polytechnic Institute (RPI) in 2011. As a graduate student, he focused on underwater image processing and object detection. Also in 2011, Matt received his bachelor’s degree in computer and systems engineering with a minor in economics from RPI.
- B. Richards, A. Hoogs, M. Dawkins, J. Taylor, S. Smith, J. Ault, and M. Seki, "Advanced Camera Technologies and Artificial Intelligence to Improve Marine Resource Surveys," in Ocean Sciences Meeting, 2020. [URL]
- A. Hoogs, M. Dawkins, B. Richards, G. Cutter, D. Hart, M. Clarke, W. Michaels, J. Crall, L. Sherrill, N. Siekierski, M. Woehlke, and K. Edwards, "An Open-Source System for Do-It-Yourself AI in the Marine Environment," in Ocean Sciences Meeting, 2020. [URL]
- A. Powell, M. Clarke, M. Dawkins, B. Richards, and A. Hoogs, "Moving Towards Machine Learning for the Analysis of Deep-Sea Imagery Collected by Autonomous Underwater Vehicle," in Ocean Sciences Meeting, 2020. [URL]
- B. Richards, O. Beijbom, M. Campbell, M. Clarke, G. Cutter, M. Dawkins, D. Edington, D. Hart, M. Hill, A. Hoogs, D. Kriegman, E. Moreland, T. Oliver, W. Michaels, M. Placentino, A. Rollo, C. Thompson, F. Wallace, I. Williams, and K. Williams, "Automated Analysis of Underwater Imagery: Accomplishments, Products, and Vision," NOAA technical memorandum NMFS PIFSC, 2019. [URL]
- J. Crall, J. Becker, P. Tunison, M. Dawkins, A. Basharat, R. Blue, M. Turek, and A. Hoogs, "Deep Learning for Small Object Detection in Satellite Infrared Imagery," in Proceedings of the MSS National Symposium on Sensor and Data Fusion, 2018.
- M. Dawkins, L. Sherrill, K. Fieldhouse, A. Hoogs, B. Richards, D. Zhang, L. Prasad, K. Williams, N. Lauffenburger, and G. Wang, "An open-source platform for underwater image and video analytics," in Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2017. Winner, Best Paper Honorable Mention. [URL]
- C. Law, J. Parham, M. Dawkins, P. Tunison, D. Stoup, R. Blue, K. Fieldhouse, M. Turek, A. Hoogs, S. Han, A. Farafard, J. Kerekes, E. Lentilucci, M. Gartley, T. Savakis, T. Rovito, S. Thomas, and C. Stansifer, "Deep learning for object detection and object-based change detection in satellite imagery," in Proceedings of the MSS National Symposium on Sensor and Data Fusion, 2017.
- M. Dawkins, R. Collins, and A. Hoogs, "Using Convolutional Neural Networks for Content-Based FMV Retrieval," in Proceedings of the MSS National Symposium on Sensor and Data Fusion, 2017.
- M. Leotta, E. Smith, M. Dawkins, and P. Tunison, "Open source structure-from-motion for aerial video," in Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2016. [URL]
- M. Dawkins, A. Basharat, J. Becker, M. Turek, and A. Hoogs, "Deep architecture for small mover detection in overhead infrared imagery," in Proceedings of the MSS National Symposium on Sensor and Data Fusion, 2016.
- M. Dawkins, Z. Sun, J. Becker, A. Basharat, A. Hoogs, and M. Turek, "Track Object Type Classification Across a Range of Scales and Types of Video," in Proceedings of the MSS National Symposium on Sensor and Data Fusion, 2016.
- M. Leotta, P. Tunison, E. Smith, and M. Dawkins, "MAP-Tk: Motion imagery Aerial Photogrammetry Toolkit," in Proceedings of the MSS National Symposium on Passive Sensors, 2015.
- K. Fieldhouse, M. Leotta, A. Basharat, R. Blue, D. Stoup, C. Atkins, L. Sherrill, B. Boeckel, P. Tunison, J. Becker, M. Dawkins, M. Woehlke, R. Collins, M. Turek, and A. Hoogs, "KWIVER: An open source cross-platform video exploitation framework," in Proceedings of the IEEE Applied Imagery Pattern Recognition Workshop, 2014. [URL]
- M. Dawkins, Z. Sun, A. Basharat, A. Perera, and A. Hoogs, "Tracking nautical objects in real-time via layered saliency detection," in SPIE Defense, Security, and Sensing Motion Imagery for ISR and Situational Awareness, 2014. [URL]
- M. Dawkins, A. Perera, and A. Hoogs, "Real-time heads-up display detection in video," in Proceedings of the IEEE Conference on Advanced Video and Signal Based Surveillance, 2014. [URL]
- M. Dawkins and A. Hoogs, "Automatic image-plane aligned obstruction detection in EO and IR video," in Proceedings of the MSS National Symposium on Passive Sensors, 2014.
- M. Dawkins, C. Stewart, S. Gallager, and A. York, "Automatic scallop detection in benthic environments," in Proceedings of the IEEE Workshop on Applications of Computer Vision, 2013. [URL]
- M. Dawkins and C. Stewart, "Scallop detection in multiple maritime environments," Rensselaer Polytechnic Institute, 2011.