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, 8 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.
← Back homeCitation
O. Arikan, Compression of Motion Capture Databases, ACM Transactions on Graphics (ACM SIGGRAPH 2006) , pp 890--897, 2006.
Results
Please see the video
Visual comparison of the compressed and original motions
Comparison with baseline methods
CMU database results
Extreme compression case. Notice that even in the still frame, you can tell two motions are different.