Sayeed Al-Aidid
Papers
1
Total Citations
4
H-Index
1
About
Dr. Sayeed Al-Aidid is a researcher whose work sits at the intersection of robotics, computer vision, and human-robot interaction. His most-cited paper, "Detection, Recognition, and Tracking Face Using 2 DoF Robot with Haar LBP Histogram" (2018), addresses a critical challenge in robotics: enabling effective face detection and tracking without relying on expensive, high-end camera systems. By integrating Haar-like features with Local Binary Pattern (LBP) histograms on a 2-degree-of-freedom robot, Dr. Al-Aidid demonstrated a cost-effective, real-time solution for visual tracking. This contribution is particularly valuable for applications in assistive robotics, surveillance, and interactive systems where affordability and accessibility are key. With 4 citations, this work has laid a foundation for further exploration into low-cost robotic vision. Dr. Al-Aidid’s research continues to push the boundaries of making intelligent, vision-guided robots more practical and widely deployable, bridging the gap between advanced algorithms and real-world hardware constraints.
Research Focus
Key Achievements
Top Papers
- 1