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A hybrid approach towards fully automatic 3D marker tracking

Motion Capture is a powerful approach to track 3D position, usually utilizing markers. Especially passive markers do not hinder natural motion. Unfortunately, such systems do not provide any information about which anatomical landmark their markers belong to. Multiple manual actions are often required to guide the tracking process. This work presents a hybrid approach for nearly fully automatic identification and tracking of such markers. It encompasses three methods for identification, using PCA-based alignment or tree-based optimization, and tracking, using a neural network with self-organizing characteristics.