Data-Driven Completion of Motion Capture Data

Abstract

We present a data-driven method for completion of corrupted marker-based motion capture data. Our novel approach is especially suitable for challenging cases, e.g. if complete marker sets of multiple body parts are missing over a long period of time. Without the need for extensive preprocessing we are able to fix missing markers across different actors and motion styles. Our approach can be used for incrementally increasing prior-databases, as the underlying search technique for similar motions scales well to huge databases.