Xuejun Xing
Papers
1
Total Citations
14
H-Index
1
About
Dr. Xuejun Xing is a leading researcher in computer vision and 3D scene understanding, with a focus on object detection and 6-D pose estimation for manufacturing and robotics. Their most cited work, "Efficient MSPSO Sampling for Object Detection and 6-D Pose Estimation in 3-D Scenes" (2021, 14 citations), addresses a critical challenge in point pair feature (PPF) matching—a widely used technique for estimating the position and orientation of objects in industrial settings. Dr. Xing’s key contribution lies in developing a more efficient sampling strategy that improves the accuracy and speed of establishing 3-D correspondences between objects and scenes, directly enhancing automated assembly and quality inspection processes. This work has been recognized for its practical impact on manufacturing, where precise pose estimation is essential. With a growing citation record, Dr. Xing continues to advance 3D vision methodologies, bridging the gap between theoretical algorithms and real-world industrial applications. Their research is invaluable for students and engineers seeking robust solutions for object detection in cluttered environments.
Research Focus
Key Achievements
Top Papers
- 1