A kNN approach based on ICP metrics for 3D scans matching: an application to the sawing process

The Canadian wood industry use sawing simulators to digitally break a log into basket of lumbers. However, those tend be computationally intensive. In some cases, this renders them impractical as decision support tools. Such case is the problem dispatching large volume several sawmills in order maximise total yield dollars. Fast machine learning metamodels were recently proposed address issue. approach needs feature extraction step which could result loss information. Conversely, it was directly make raw information, available 3D scans logs typically used by recent sawmill simulator, retain that Here, we improve upon method reducing computational cost incidental with processing scans.