Seokwon Yeom

Daegu University

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

2
H-Index
2
Papers
19
Total Citations
10
Avg Citations/Paper
🏆 Most Cited Paper
Person-Specific Face Detection in a Scene with Optimum Composite Filtering and Colour-Shape Information
14 citations · 2013
📈 Most Prolific Year: 2013 (1 Papers)
🤝 Key Collaborators: 1
🏛 Institutions: Daegu University

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 15 days ago