Automatic Extraction of Go Game Positions from Images: a Multi-Strategical Approach to Constrained Multi-Object Recognition

Here, we present a constrained object recognition task that has been robustly solved largely with simple machine learning methods, using a small corpus of about 100 images taken under a variety of lighting conditions. The task was to analyze images from a hand-held mobile phone camera showing an endgame position for the Japanese board game Go. The presented system would already be sufficient to reconstruct the full Go game record from a video record of the game, and thus is complementary to (Seewald, 2003) which focuses on solving the same task using 1 

• Type: Journal
• Year: 2010
• Where: AAI
• Authors: Alexander K. Seewald
• Keywords: AAI 2010, Algorithms, Go Game Record, Hand-held Mobile Phone, Object Recognition Task