Lingxuan Tang
Papers
1
Total Citations
8
H-Index
1
About
Dr. Lingxuan Tang is a researcher advancing the fields of computer vision and human-robot interaction, with a focus on real-time human body recognition and spatial positioning. Her most-cited work, "Research on Human Body Recognition and Position Measurement Based on AdaBoost and RGB-D" (2020, 8 citations), tackles a critical bottleneck in robotics: the trade-off between recognition speed and accuracy. By integrating the AdaBoost algorithm with RGB-D sensor data, Dr. Tang developed a method that enhances both the precision and efficiency of detecting and localizing human targets in dynamic environments. This contribution is foundational for enabling more responsive and intuitive machine-human interactions, particularly in assistive robotics and autonomous systems. Her research addresses the persistent challenge of achieving reliable target identification under real-world constraints, laying groundwork for safer and more adaptive robotic platforms. Dr. Tang’s work is cited by peers exploring sensor fusion and real-time tracking, underscoring its relevance in bridging computational efficiency with practical deployment. Her insights continue to inform next-generation systems where seamless human-robot collaboration is paramount.
Research Focus
Key Achievements
Top Papers
- 1