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Combining sampling and autoregression for motion synthesis
Proceedings Computer Graphics International, 2004.
We present a novel approach to motion synthesis. We show that by splitting sequences into segments we can create new sequences with a similar look and feel to the original. Copying segments of the original data generates a sequence which maintains detailed characteristics. By modelling each segment using an autoregressive process we can introduce new segments and therefore unseen motions. These statistical models allow a potentially infinite number of new segments to be generated. We show that
doi:10.1109/cgi.2004.1309255
dblp:conf/cgi/OziemCDGT04
fatcat:xinxydhyjbc23pucad5pfo547m