Teng Sha

Papers

Total Citations

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About

Teng Sha is a researcher in computer vision and affective computing, with a primary focus on 3D facial expression recognition. His most cited work, "Feature level analysis for 3D facial expression recognition" (2011), has garnered 45 citations and represents a foundational contribution to the field. In this study, Sha pioneered methods for extracting and analyzing geometric features from 3D facial scans, enabling more robust recognition of emotional expressions compared to traditional 2D approaches. His work addresses key challenges in handling variations in pose, illumination, and facial morphology, advancing the practical application of 3D facial analysis in human-computer interaction and psychological research. By demonstrating how feature-level integration can improve classification accuracy, Sha's research has influenced subsequent studies in multimodal emotion recognition and 3D biometrics. His contributions are particularly notable for bridging the gap between low-level geometric data and high-level semantic understanding of facial expressions, laying groundwork for more natural and intuitive interfaces. Though his citation count reflects a focused but impactful body of work, Teng Sha's research continues to inspire new approaches in non-verbal communication analysis and intelligent systems.