Seokwon Yeom
Papers
2
Total Citations
19
H-Index
2
About
Seokwon Yeom’s research focuses on the intersection of computer vision, biometrics, and intelligent surveillance, with a particular emphasis on face detection and recognition at a distance. His work addresses the formidable challenges of identifying individuals in degraded, long-distance images—where low resolution, blurring, and noise often compromise accuracy. Yeom’s major contributions include the development of person-specific face detection methods that integrate optimum composite filtering with colour-shape information, a technique that enhances detection reliability in complex scenes. He also pioneered photon-counting linear discriminant analysis for face recognition at a distance, a novel approach that improves performance under challenging imaging conditions. Although his citation counts are modest—14 citations for his 2013 paper and 5 for his 2012 work—these studies represent foundational efforts in a niche but critical area of surveillance and robot vision. Yeom’s research is particularly notable for its practical applications in security systems and machine interfaces, where robust identification from a distance is essential. His work continues to inspire further exploration into advanced filtering and statistical methods for long-range biometric recognition.
Research Focus
Key Achievements
Top Papers
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