Papers
5
Total Citations
67
H-Index
4
About
Hu He’s research spans computer vision, robotics, and advanced materials, with a focus on enabling autonomous systems to perceive and interact with their environments. His early work on unaided stereo vision for pose estimation (42 citations) laid the groundwork for low-cost, accurate robot localization in SLAM tasks, a critical contribution to field robotics. He advanced interactive segmentation by fusing colour and depth cues, and later tackled large-scale 3D semantic mapping for autonomous driving, demonstrating how dense semantic models improve navigation and localization. Beyond vision, He innovated in flexible electronics, developing CNTs/PDMS nanocomposite strain sensors (5 citations) for human motion detection and soft robotics—a cross-disciplinary leap that highlights his versatility. His work on automatic object segmentation using multiview stereo further underscores his commitment to practical robotic perception. With a career that bridges classical computer vision, semantic scene understanding, and novel sensor materials, Hu He has made impactful contributions that resonate across robotics, autonomous vehicles, and wearable technology.
Research Focus
Key Achievements
Top Papers
- 1Unaided stereo vision based pose estimation42 citations · 2010
- 2Graphcut-based interactive segmentation using colour and depth cues10 citations · 2010
- 3Nonparametric semantic segmentation for 3D street scenes6 citations · 2013
- 4Flexible strain sensors based on CNTs/PDMS nanocomposite5 citations · 2018
- 5Towards Automatic Object Segmentation with Sequential Multiple Views4 citations · 2011