Yuqing Huo
Papers
1
Total Citations
2
H-Index
1
About
Yuqing Huo is a researcher at the forefront of computer vision and human motion analysis, with a particular focus on 3D human pose estimation and its applications in sports and rehabilitation. Her most-cited work, "A Method for 3D Human Pose Estimation and Similarity Calculation in Tai Chi Videos" (2023), addresses a critical challenge in the field: accurately estimating three-dimensional poses from video sequences where human movement speed varies significantly. Unlike conventional frame-by-frame approaches, Huo’s method integrates temporal dynamics to enhance precision, achieving notable improvements in pose similarity calculations for complex, fluid motions like Tai Chi. This contribution has direct implications for robotics, virtual reality, and physical therapy, where understanding nuanced human movement is essential. With 2 citations already, her work is gaining traction among researchers exploring motion capture and human-robot interaction. Huo’s research bridges the gap between computer vision algorithms and real-world applications, offering a robust framework for analyzing dynamic poses. Her innovative approach to handling variable movement speeds marks her as a promising voice in advancing 3D human pose estimation, with potential to impact fields from sports science to assistive technology.
Research Focus
Key Achievements
Top Papers
- 1