Daniel Doyle

U.S. Air Force Institute of Technology, Virginia Tech

Papers

Total Citations

H-Index

About

Daniel Doyle is a researcher working at the intersection of computer vision, robotics, and autonomous systems, with a particular focus on real-time tracking and planetary exploration technologies. His most cited work, "Optical flow background subtraction for real-time PTZ camera object tracking" (2013, 14 citations), addresses a critical challenge in security, sports, and navigation systems: enabling pan/tilt/zoom cameras to autonomously track moving objects in dynamic environments. By combining optical flow with background subtraction, Doyle’s approach enhances the accuracy and responsiveness of PTZ systems, laying groundwork for more intelligent surveillance and measurement tools. More recently, Doyle has contributed to space exploration, co-authoring "IR based local tracking system Assessment for planetary exploration missions" (2020, 2 citations). This work supports NASA’s vision for deploying UAVs on Mars and Titan, assessing infrared-based tracking for autonomous navigation in extreme extraterrestrial terrains. Though his citation counts are modest, Doyle’s research bridges practical computer vision applications with cutting-edge aerospace challenges, demonstrating versatility and forward-thinking. His work is particularly relevant for students and researchers interested in real-time tracking, autonomous navigation, and the growing role of aerial vehicles in planetary science.