A Database Architecture for Real-Time Motion Retrieval

Over the past decade, many research fields have realized the benefits of motion capture data, leading to an exponential growth of the size of motion databases. Consequently indexing, querying, and retrieving motion capture data have become important considerations in the usability of such databases. Our aim is to efficiently retrieve motion from such databases in order to produce real-time animation. For that purpose, we propose a new database architecture which structures both the semantic and raw data contained in motion data. The performance of the overall architecture is evaluated by measuring the efficiency of the motion retrieval process, in terms of the mean time access to the data.

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