Kan Ren

Nanjing University of Science and Technology

Papers

Total Citations

H-Index

About

Kan Ren is a researcher specializing in computer vision and optical metrology, with a particular focus on improving the accuracy and calibration of sensor systems. His work centers on the integration of laser range finders with visual cameras, addressing fundamental challenges in 3D spatial measurement. Ren’s most cited paper, "Calibration of a single-point laser range finder and a camera" (2018, 6 citations), introduces a precise calibration method that enhances the synergy between these two sensor types, enabling more reliable distance estimation in real-world applications. Building on this, his 2019 study, "A new method for increasing accuracy of distance measurement based on single visual camera" (5 citations), proposes an innovative approach to boost measurement precision using only a monocular camera, reducing dependency on additional hardware. Though his citation counts are modest, Ren’s contributions are significant for fields like robotics, autonomous navigation, and industrial inspection, where accurate distance sensing is critical. His work demonstrates a clear trajectory toward cost-effective, high-accuracy sensing solutions, making him a valuable figure for students and researchers exploring sensor fusion and calibration techniques in computer vision.