Tianyi Zou
Papers
2
Total Citations
7
H-Index
2
About
Tianyi Zou is a researcher specializing in human motion analysis and autonomous robotic perception, with a focus on improving human-robot interaction and campus automation. Their key contributions include developing a novel method for fast identification of human skeleton-marker models using stochastic gradient descent, enabling more convenient and accurate motion capture for biomechanical analyses. This work, published in 2020, has garnered 4 citations and provides a foundation for efficient kinematic modeling in optical motion capture systems. Additionally, Zou led the design and implementation of a campus pedestrian detection system for the unmanned sanitation robot “Sweeper” at Shanghai Sanda University. By employing blob analysis on over 300 campus images, they enhanced the robot’s target detection and cleaning capabilities, a study that has earned 3 citations. This practical application demonstrates Zou’s ability to bridge theoretical algorithms with real-world robotic systems. Their work contributes to advancing autonomous navigation and human motion understanding, with potential impacts on assistive robotics, sports science, and smart campus technologies.
Research Focus
Key Achievements
Top Papers
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- 2