Papers
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Total Citations
17
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About
Xinge Liu is a researcher whose work sits at the intersection of affective computing, visual perception, and human-robot interaction. Her primary research focus is on understanding how emotional expressions are recognized in non-human faces, particularly in cartoons and animated characters—a field with growing relevance for social robotics, animation, and digital media. In her most cited work, "The Influence of Key Facial Features on Recognition of Emotion in Cartoon Faces" (2021, 17 citations), Liu systematically investigated which facial features—such as eyes, eyebrows, or mouth—are most critical for accurately identifying emotions like happiness, sadness, or anger in stylized cartoon faces. This study provided foundational insights for designing more emotionally expressive social robots and for improving character animation in entertainment and education. By bridging cognitive science and computer graphics, Liu’s contributions help explain why humans intuitively read emotions in simplified faces, a phenomenon widely exploited in emoji, virtual assistants, and animated films. Her work has implications for user interface design, autism research, and the development of emotionally intelligent AI.
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