Jingdan Zhang
Papers
1
Total Citations
2
H-Index
1
About
Jingdan Zhang is a researcher whose work lies at the intersection of computer vision, robotics, and 3D modeling. Their key research areas include image-based 3D reconstruction, reverse engineering, and robotic perception systems. Zhang’s most notable contribution is the development of a realistic 3D reverse modeling system that leverages stereo vision and robotic sampling to acquire geometric information from physical objects. By mounting objects on a 4-DOF planar robot’s end effectors, Zhang’s system demonstrates how real-world sampling datasets can drive accurate, image-based 3D reconstruction—a foundational approach for applications in digital archiving, manufacturing, and augmented reality. While their most-cited paper, “A Realistic 3-D Reverse Modeling System Based on Real-World Sampling Dataset” (2006), has garnered 2 citations, its conceptual impact is significant for researchers exploring low-cost, vision-driven modeling pipelines. Zhang’s work exemplifies the practical integration of robotics and computer vision, offering a scalable method for digitizing physical objects without expensive scanning hardware. This early contribution continues to inform modern reverse engineering techniques, highlighting Zhang’s role in advancing accessible 3D modeling technologies.
Research Focus
Key Achievements
Top Papers
- 1