James Dokyoon Kim
Papers
1
Total Citations
22
H-Index
1
About
James Dokyoon Kim is a researcher whose work centers on sensor fusion and calibration, with a particular emphasis on integrating Time-of-Flight (ToF) depth cameras with conventional imaging systems. His most notable contribution is the development of a novel 2.5D calibration pattern for extrinsic calibration of ToF and camera fusion systems, introduced in his highly cited 2011 paper (22 citations). This work addresses a critical gap in the field: while previous research had extensively modeled intrinsic errors and noise in ToF cameras, Kim recognized that accurate extrinsic calibration—aligning the coordinate systems of depth and color sensors—was equally essential for reliable fusion. His 2.5D pattern approach provided a practical, robust solution that improved the accuracy of depth-to-color mapping, enabling more effective use of ToF cameras in applications like 3D reconstruction and augmented reality. By tackling this overlooked calibration challenge, Kim helped advance the practical deployment of multimodal sensing systems, making his work a valuable reference for researchers working on sensor integration and computer vision.
Research Focus
Key Achievements
Top Papers
- 1