Combining Sampling and Autoregression for Motion Synthesis

DJ Oziem, NW Campbell, CJ Dalton, DP Gibson, BT Thomas

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)


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 this system can model complicated nonstationary sequences which a single ARP is unable to do
Translated title of the contributionCombining Sampling and Autoregression for Motion Synthesis
Original languageEnglish
Title of host publicationProceedings of the Computer Graphics International Conference
PublisherIEEE Computer Society
Pages510 - 513
Number of pages4
ISBN (Print)0769521711
Publication statusPublished - Jun 2004

Bibliographical note

Conference Organiser: IEEE Computer Society


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