Chih-Hsin Wang

National Taiwan University of Science and Technology

Papers

Total Citations

H-Index

About

Chih-Hsin Wang is a researcher whose work bridges computer vision and human-robot interaction, with a particular focus on face recognition and tracking technologies. His most cited paper, "Real-Time Multi-Face Recognition and Tracking Techniques Used for the Interaction between Humans and Robots" (2011), introduces a novel classification method called the nearest feature line (NFL) for face recognition. This approach captures more variations in face images than traditional feature points, significantly expanding the capacity of available training data and improving recognition accuracy in dynamic environments. The NFL method has been cited 294 times, reflecting its substantial impact on the field. Wang’s contributions are particularly notable for enabling real-time, multi-face tracking that facilitates seamless human-robot interaction, a critical advancement for socially assistive robots and autonomous systems. His work has been recognized for its practical applications in robotics, where robust face recognition is essential for natural communication. By addressing key challenges in variability and computational efficiency, Wang has provided foundational techniques that continue to influence research in biometrics and interactive robotics.