Seungji Yang
Papers
1
Total Citations
24
H-Index
1
About
Seungji Yang is a leading researcher in computer vision and video processing, with a particular focus on robust video stabilization and camera motion estimation. His most-cited work, "Robust Video Stabilization Using Particle Keypoint Update and l1-Optimized Camera Path" (2017, 24 citations), introduces an adaptive camera path estimation method that effectively removes shaky artifacts from digital video. The algorithm employs robust feature detection through a three-step process—including particle keypoint updating and l1-optimized camera path smoothing—to produce stable, high-quality footage even in challenging capture conditions. This contribution is especially valuable for consumer cameras, action cams, and mobile devices where mechanical stabilization is limited. Yang’s research addresses the critical challenge of acquiring visually smooth video from handheld or moving platforms, directly impacting fields like augmented reality, surveillance, and cinematography. His work is recognized for combining computational efficiency with practical robustness, making it applicable to real-time systems. With ongoing influence in video enhancement and motion analysis, Seungji Yang continues to advance the state of the art in digital video stabilization.
Research Focus
Key Achievements
Top Papers
- 1