Amirhossein Feizi
Papers
1
Total Citations
2
H-Index
1
About
Amirhossein Feizi is a researcher at the forefront of human-robot interaction, specializing in real-time imitation systems and affective computing. His most cited work, "Real-Time Imitation of Human Head Motions, Blinks and Emotions by Nao Robot: A Closed-Loop Approach" (2023), introduces a groundbreaking closed-loop framework that enables a Nao robot to mimic human head movements, blinks, and emotional expressions in real time. By integrating MediaPipe for precise pose estimation and DeepFace for emotion recognition, Feizi’s system bridges the gap between natural human behavior and robotic response, significantly enhancing the intuitiveness of human-robot communication. This contribution has garnered attention for its practical applications in assistive robotics and social interaction studies. With 2 citations to date, his work demonstrates early impact in a rapidly evolving field. Feizi’s research not only advances technical capabilities in computer vision and emotion detection but also lays the groundwork for more empathetic and responsive robotic systems, making him a promising voice in the next generation of human-robot collaboration.
Research Focus
Key Achievements
Top Papers
- 1