Oscar E. Perez-Cham
Papers
1
Total Citations
11
H-Index
1
About
Oscar E. Perez-Cham is a researcher specializing in embedded systems, real-time video tracking, and bio-inspired optimization algorithms. His work focuses on developing low-power, high-performance hardware-software co-designs for computer vision applications, particularly leveraging System-on-Chip Field-Programmable Gate Arrays (SoC-FPGAs) to achieve efficient real-time processing. His most cited paper, "Design of a Low-Power Embedded System Based on a SoC-FPGA and the Honeybee Search Algorithm for Real-Time Video Tracking" (2022, 11 citations), introduces a novel approach that combines the Honeybee Search Algorithm—a swarm intelligence technique—with reconfigurable hardware to address the persistent challenges of video tracking, such as occlusion, illumination changes, and computational constraints. This work demonstrates how bio-inspired methods can enhance tracking robustness while maintaining low power consumption, making it relevant for robotics, unmanned vehicles, and automation. Perez-Cham’s contributions bridge the gap between algorithmic innovation and practical embedded deployment, offering scalable solutions for real-world vision systems. His research continues to advance the frontier of intelligent, energy-efficient autonomous systems.
Research Focus
Key Achievements
Top Papers
- 1