Vo Duc My
Papers
4
Total Citations
30
H-Index
3
About
Vo Duc My is a leading researcher in human-robot interaction and computer vision, with a focus on enabling mobile robots to perceive and engage with humans in real-world environments. His work centers on real-time face tracking, pose estimation, and robust face detection under challenging conditions—such as varying illumination and free human movement—using adaptive correlation filters and depth-based segmentation. These contributions have been cited over 30 times, reflecting their practical value for autonomous robotics. My also advanced image segmentation by developing superpixel algorithms that leverage gradient maps on RGB-D datasets, improving computational efficiency for downstream tasks. His research bridges the gap between algorithmic accuracy and real-time performance on resource-constrained robot platforms, making him a key figure in the field. Notably, his 2013 paper on face tracking and pose estimation for human-robot interaction stands out as a foundational work, demonstrating how mobile robots can maintain natural, responsive interactions with people in uncontrolled settings.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3Superpixel segmentation based gradient maps on RGB-D dataset5 citations · 2015
- 4Superpixel segmentation based gradient maps on RGB-D dataset3 citations · 2015