Chung-Lin Huang

Papers

Total Citations

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About

Chung-Lin Huang is a leading researcher in computer vision and human-robot interaction (HRI), with a focus on enabling machines to perceive and respond to human presence and emotion. His work bridges deep learning and robotics, particularly through the development of real-time identification and recognition systems. Huang’s most cited paper, “Human Object Identification for Human-Robot Interaction by Using Fast R-CNN” (2018, 40 citations), introduces a simplified region-based convolutional network that achieves state-of-the-art pedestrian detection, a critical step for robots navigating human environments. Complementing this, his study “Facial Expression Recognition for Human-Robot Interaction” (2017, 20 citations) tackles the challenge of individual variability in emotional expression, proposing robust FER methods for assistant robots in close-contact scenarios. These contributions have advanced the practical deployment of socially aware robots, with his work cited for its efficiency and applicability in real-world settings. Huang’s research is particularly notable for addressing the non-trivial problem of person-specific expression recognition, laying groundwork for more intuitive human-robot collaboration.