Deokkyu Kim
Papers
1
Total Citations
2
H-Index
1
About
Deokkyu Kim is a researcher in autonomous systems, with a primary focus on multi-sensor fusion for perception in robotics and autonomous driving. His work centers on the critical challenge of extrinsic parameter calibration, which is essential for integrating different sensor modalities like LiDAR and cameras. Kim’s most cited paper, “Extrinsic parameter calibration of 2D LiDAR-camera using edge matching and removal of infrared cut filter” (2019), proposes a novel calibration method that improves alignment accuracy by leveraging edge matching and a hardware modification—removing the infrared cut filter from the camera. This practical approach addresses a foundational step in sensor fusion, directly supporting the development of reliable perception systems for unmanned robots and autonomous vehicles. While his citation count is still growing, his contribution is notable for its hands-on, engineering-driven solution to a persistent problem in the field. Kim’s work is particularly relevant for researchers and students working on sensor integration, calibration pipelines, and the early stages of autonomous system design, where precise sensor alignment is a prerequisite for higher-level tasks like object detection and mapping.
Research Focus
Key Achievements
Top Papers
- 1