Ting Han

Papers

Total Citations

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About

Ting Han is a rising researcher in computer vision and 3D perception, with a focus on point cloud processing and multi-camera calibration. Their most-cited work, "A Survey of Point Cloud Completion" (2024, 32 citations), provides a comprehensive overview of methods for estimating complete 3D point clouds from partial data—a critical task for applications in remote sensing, medical imaging, and robotics. This survey has become a key reference for researchers tackling the challenge of disordered and incomplete point cloud data. Han’s notable contribution, "NMC3D: Non-Overlapping Multi-Camera Calibration Based on Sparse 3D Map" (2024, 4 citations), addresses a practical problem in unmanned systems and robotics by enabling accurate calibration of multi-camera setups without requiring overlapping fields of view. This work supports the development of robust perception systems for autonomous navigation and control. With a growing citation impact and a focus on bridging theoretical advances with real-world applications, Han is establishing a reputation for advancing 3D vision technologies that enhance the capabilities of intelligent systems.