Hai‐Hong Phan

Papers

Total Citations

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About

Hai-Hong Phan is a researcher advancing the intersection of computer vision and human-robot interaction. Their primary research areas include skeleton-based action recognition, robot vision, and affective computing—specifically integrating face and emotion recognition into robotic systems. Phan’s most cited work, "KFSENet: A Key Frame-Based Skeleton Feature Estimation and Action Recognition Network for Improved Robot Vision with Face and Emotion Recognition" (2022), introduces a novel network that leverages key frame selection to efficiently estimate skeleton features and recognize actions, while simultaneously incorporating facial and emotional cues. This integrated approach enables social robots to engage in more personalized, context-aware interactions, bridging the gap between raw visual data and meaningful social behavior. With 14 citations, this paper has already attracted attention for its practical contribution to making robots more perceptive of human intent and affect. Phan’s work is notable for its focus on real-world applicability, aiming to enhance robot vision systems in assistive and collaborative settings. Their research holds promise for advancing socially intelligent robotics, where machines can better understand and respond to human actions and emotions.