Fisher vector encoding of micro color features for (real world) jigsaw puzzles
In this work we propose a computationally efficient yet effective color encoding scheme for the purpose of jigsaw puzzle solving. Our contribution is twofold: (i) First of all, we show that a Fisher vector encoding gives superior performance over the commonly used compatibility descriptor of stacked color values. (ii) Furthermore, we show experimentally on synthetic and real-world data that our proposed color encoding is more robust in the presence of noise, as compared to three widely used features. Due to the robustness of our proposed descriptor we also anticipate its use to yield performance improvements in other applications, e.g., for the virtual reconstruction of hand-torn documents and archaeological findings.