Papers
2
Total Citations
34
H-Index
2
About
Xin Yuan is a researcher at the forefront of privacy-preserving computer vision and human-robot interaction. His primary research areas include single-pixel imaging, human pose estimation, and robotic manipulation, with a strong focus on addressing critical challenges in data security and healthcare monitoring. Yuan’s most notable contribution is his pioneering work on image-free single-pixel keypoint detection for human pose estimation, which eliminates the need to capture identifiable human images, thereby safeguarding privacy while maintaining high accuracy—a paper that has already garnered 30 citations since its 2024 publication. This breakthrough has significant implications for surveillance, robot vision, and telemedicine. Additionally, Yuan developed a face tracking strategy using manipulability analysis of a 7-DOF robot arm and head motion intention ellipsoids, designed to enable non-invasive patient monitoring in intensive care units. This work, cited 4 times, addresses the gap in instruments capable of accurately recording facial expressions and eye motions for detecting pain, agitation, or delirium. Yuan’s research is characterized by its interdisciplinary approach, merging computer vision, robotics, and healthcare to create safer, more ethical technologies.
Research Focus
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Top Papers
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