Zheng-Yang Huang
Papers
1
Total Citations
3
H-Index
1
About
Zheng-Yang Huang is a researcher whose early work focused on advancing three-dimensional object identification and robotic perception. His most-cited paper, "A Case Study of Object Identification Using a Kinect Sensor" (2013), explores the transformative potential of affordable depth-sensing technology—specifically the Kinect sensor—for robotic object recognition. By leveraging the Point Cloud Library (PCL) and the Iterative Closest Point (ICP) algorithm, Huang demonstrated how 3D point cloud processing could enable more accurate and accessible object identification compared to traditional RGB camera and LIDAR systems. This work contributed to the broader adoption of consumer-grade sensors in robotics and computer vision research. Though his citation count is modest, Huang’s study serves as a practical case reference for researchers integrating low-cost depth sensors into robotic perception pipelines. His contributions highlight the shift toward democratized 3D sensing technology, making advanced object identification more feasible for a wider range of applications.
Research Focus
Key Achievements
Top Papers
- 1A Case Study of Object Identification Using a Kinect Sensor3 citations · 2013