Dan‐Yang Wang
Papers
1
Total Citations
2
H-Index
1
About
Dan-Yang Wang is a researcher focused on advancing human-computer interaction through intelligent gesture recognition systems, particularly for service robotics. Their most-cited work, "A Gesture Recognition Method Based on YCbCr and SURF for Service Robot Interaction" (2021), addresses critical challenges in real-world applications—such as complex backgrounds, occlusions, and varying illumination—that hinder reliable gesture detection. By integrating YCbCr color space for robust skin segmentation with SURF feature extraction, Wang developed a method that enhances recognition accuracy under adverse conditions, directly improving the responsiveness and usability of service robots in dynamic environments. While this paper has garnered 2 citations, it represents a foundational contribution to the field, demonstrating Wang’s ability to tackle practical obstacles in human-robot interaction. Their work underscores a commitment to making robotic systems more intuitive and accessible, with potential applications spanning assistive technologies, smart homes, and industrial automation. Wang’s research continues to inspire efforts toward seamless, natural communication between humans and machines.
Research Focus
Key Achievements
Top Papers
- 1