Inhye Yoon

Papers

Total Citations

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About

Inhye Yoon’s research lies at the intersection of computer vision and video processing, with a particular focus on robust feature detection and video stabilization. Her 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 leverages robust feature detection to eliminate shaky artifacts in digital video. This three-step algorithm—featuring robust feature detection, particle keypoint updating, and l1-optimized path smoothing—offers a practical solution for improving video quality across various camera types. Yoon also contributed a comprehensive survey, “Recent Advances in Feature Detectors and Descriptors: A Survey” (2016, 11 citations), which systematically analyzes how different image environments affect the performance of modern feature extraction methods. This work provides valuable guidance for researchers selecting appropriate detectors and descriptors for diverse applications in image understanding and computer vision. Through these contributions, Yoon has advanced the reliability of video stabilization techniques and deepened the understanding of feature detection challenges, making her work relevant for both academic researchers and practitioners developing robust vision systems.