Jiangtao Lu
Papers
1
Total Citations
2
H-Index
1
About
Jiangtao Lu is a researcher focused on advancing human-computer interaction, particularly through gesture recognition and service robotics. His most cited work, "A Gesture Recognition Method Based on YCbCr and SURF for Service Robot Interaction" (2021), addresses critical challenges in real-world gesture recognition—such as complex backgrounds, occlusions, and varying illumination—by combining YCbCr color space segmentation with SURF feature matching. This contribution enhances the robustness and reliability of gesture-based interfaces for service robots, a key area in assistive and autonomous systems. With 2 citations, this paper has laid groundwork for improving interaction experiences in dynamic environments. Lu’s research sits at the intersection of computer vision, robotics, and human-centered design, aiming to make robot interaction more intuitive and accessible. His work is particularly relevant for students and researchers exploring non-verbal communication in human-robot interaction, offering practical solutions to persistent visual recognition problems. Through this and related studies, Lu contributes to the broader goal of seamless, natural interfaces that can operate reliably in uncontrolled, everyday settings.
Research Focus
Key Achievements
Top Papers
- 1