A New Approach to an Old Problem: The Reconstruction of a Go Game through a Series of Photographs

TL;DR

This paper presents a novel method for automatically reconstructing the sequence of moves in a Go game from a series of photographs by detecting grid lines, tracking movements, estimating viewpoint, and identifying stones.

Contribution

It introduces a comprehensive algorithm that combines grid detection, viewpoint estimation, and stone recognition to reconstruct Go game sequences from images, improving automation.

Findings

Successfully identified grid lines and tracked their movements.

Estimated observer's viewpoint to correct projection distortions.

Automatically reconstructed complete move sequences from photographs.

Abstract

Given a series of photographs taken during a Go game, we describe the techniques we successfully employ for pinpointing the grid lines of the Go board and for tracking their small movements between consecutive photographs; then we discuss how to approximate the location and orientation of the observer's point of view, in order to compensate for projection effects. Finally we describe the different criteria that jointly form the algorithm for stones' detection, thus enabling us to automatically reconstruct the whole move sequence.