King Yiu Tam
Papers
1
Total Citations
20
H-Index
1
About
King Yiu Tam is a researcher whose work bridges computer vision and practical game-playing systems. His primary research areas include image segmentation, pattern recognition, and automated visual analysis for board games. Tam’s most notable contribution is his pioneering work on the automatic segmentation of populated chessboards from lower-angle perspectives—a challenging problem in real-world vision systems. His 2008 paper on this topic, which has garnered 20 citations, provides a robust method for extracting grid elements from cluttered, non-ideal images. This work is foundational for chess video annotation, content-based indexing, and the development of chess-playing robots. By solving a critical preprocessing step, Tam enabled more accurate coordinate extraction and content analysis in prototype vision systems. His research demonstrates a keen ability to address practical, real-world constraints—such as camera angle and piece occlusion—that often hinder automated game analysis. While his citation count reflects a focused but impactful contribution, Tam’s work stands as a key reference for researchers developing intelligent systems for board game automation and video content understanding.
Research Focus
Key Achievements
Top Papers
- 1