Semi Jeon
Papers
2
Total Citations
35
H-Index
2
About
Semi Jeon is a computer vision researcher whose work focuses on video stabilization and robust feature extraction for image understanding. Jeon’s most notable contribution is a novel approach to removing shaky artifacts from digital video, detailed in the 2017 paper “Robust Video Stabilization Using Particle Keypoint Update and l1-Optimized Camera Path.” This method, which has earned 24 citations, introduces an adaptive camera path estimation technique that leverages robust feature detection to produce smooth, stabilized footage. By combining particle filtering for keypoint tracking with l1-optimization for camera path smoothing, Jeon’s work addresses a critical challenge for consumer and professional digital cameras alike. Additionally, Jeon authored a comprehensive 2016 survey on recent advances in feature detectors and descriptors, which has garnered 11 citations. This survey systematically analyzes how different image environments affect the detection of robust local features, providing a valuable resource for researchers in image understanding and computer vision. Through these contributions, Jeon has advanced both the practical application of video stabilization and the theoretical understanding of feature extraction methods.
Research Focus
Key Achievements
Top Papers
- 1
- 2Recent Advances in Feature Detectors and Descriptors: A Survey11 citations · 2016