Kevin Hammond
Papers
1
Total Citations
13
H-Index
1
About
Kevin Hammond is a computer scientist whose research spans the critical intersection of computer vision, autonomous systems, and real-time embedded control. His most cited work, "Using Mean-Shift Tracking Algorithms For Real-Time Tracking Of Moving Images On An Autonomous Vehicle Testbed Platform" (2007, 13 citations), introduces novel computer vision algorithms that exploit variable kernels for robust object tracking in video sequences. This foundational study, part of a long-term investigation into (semi-)autonomous vehicle design, demonstrates how advanced tracking can be achieved in real-time on physical testbed platforms. Hammond's contributions are particularly notable for bridging theoretical computer vision techniques with practical, hardware-constrained implementations—a challenge central to modern autonomous driving and robotics. His work on mean-shift tracking has provided a benchmark for subsequent research in adaptive kernel-based tracking, influencing both academic studies and applied engineering projects. By focusing on the real-time constraints of moving platforms, Hammond has helped advance the feasibility of autonomous navigation systems, making his research a valuable reference for students and engineers working at the frontier of intelligent vehicles and embedded computer vision.
Research Focus
Key Achievements
Top Papers
- 1