Papers
1
Total Citations
12
H-Index
1
About
Kang Yi is a researcher in computer vision and robotics, with a primary focus on human action recognition for assistive technologies. His work addresses a core challenge in personal robotics: enabling machines to observe and interpret human daily activities in real time. Yi’s most cited paper, “Human action recognition using key poses and atomic motions” (2015, 12 citations), introduces an intuitive framework that models human activities as sequences of key poses and atomic motions. This approach simplifies complex action recognition by breaking movements into fundamental, recognizable components, making it more computationally efficient and practical for robotic systems. By bridging the gap between low-level motion data and high-level activity understanding, Yi’s contributions support the development of robots that can automatically react to human behavior, enhancing human-robot interaction. His work is particularly valuable for researchers in assistive robotics, human-computer interaction, and video analysis, offering a structured method for recognizing actions in everyday environments.
Research Focus
Key Achievements
Top Papers
- 1Human action recognition using key poses and atomic motions12 citations · 2015