Compression of motion capture databases

Abstract

We present a lossy compression algorithm for large databases of motion capture data. We approximate short clips of motion using Bezier curves and clustered principal component analysis. This approximation has a smoothing effect on the motion. Contacts with the environment (such as foot strikes) have important detail that needs to be maintained. We compress these environmental contacts using a separate, JPEG like compression algorithm and ensure these contacts are maintained during decompression.Our method can compress 6 hours 34 minutes of human motion capture from 1080 MB data into 35.5 MB with little visible degradation. Compression and decompression is fast: our research implementation can decompress at about 1.2 milliseconds/frame, 7 times faster than real-time (for 120 frames per second animation). Our method also yields smaller compressed representation for the same error or produces smaller error for the same compressed size.

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Index Terms

• Computing methodologies

  • Artificial intelligence

    • Computer vision

      • Image and video acquisition

        • Motion capture

  • Computer graphics

    • Animation

      • Motion capture

      • Motion processing

    • Shape modeling

      • Parametric curve and surface models

      • Volumetric models

• Theory of computation

  • Randomness, geometry and discrete structures