Dustin Richmond
Papers
1
Total Citations
17
H-Index
1
About
Dustin Richmond is a researcher whose work sits at the intersection of reconfigurable computing, FPGA-based acceleration, and real-time embedded systems. His research focuses on bridging the gap between high-level programming models and the raw performance of hardware, particularly through the use of OpenCL for FPGAs. His most cited work, "Real-time 3D reconstruction for FPGAs: A case study for evaluating the performance, area, and programmability trade-offs of the Altera OpenCL SDK" (2014, 17 citations), is a landmark case study that demonstrated how low-cost depth sensors could be used for real-time 3D reconstruction without requiring a powerful GPU. This work directly addressed a critical bottleneck in augmented reality and mobile robotics, showing that FPGAs could deliver comparable performance with significantly lower power and form factor constraints. By systematically evaluating the trade-offs between performance, area, and programmability, Richmond provided a practical roadmap for developers seeking to deploy complex computer vision algorithms on embedded hardware. His contributions have been instrumental in making real-time 3D perception feasible for resource-constrained platforms, opening new possibilities for autonomous systems and interactive applications.
Research Focus
Key Achievements
Top Papers
- 1