Combining Sampling and Autoregression for Motion Synthesis

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

Combining Sampling and Autoregression for Motion Synthesis

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

Bristol Robotics Laboratory

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

Abstract

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 contribution	Combining Sampling and Autoregression for Motion Synthesis
Original language	English
Title of host publication	Proceedings of the Computer Graphics International Conference
Publisher	IEEE Computer Society
Pages	510 - 513
Number of pages	4
ISBN (Print)	0769521711
Publication status	Published - Jun 2004

Bibliographical note

Conference Organiser: IEEE Computer Society

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http://www.cs.bris.ac.uk/Publications/Papers/2000122.pdf

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@inproceedings{3e753fa91e754e0d9c299317c873f249,

title = "Combining Sampling and Autoregression for Motion Synthesis",

abstract = "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",

author = "DJ Oziem and NW Campbell and CJ Dalton and DP Gibson and BT Thomas",

note = "Conference Organiser: IEEE Computer Society",

year = "2004",

month = jun,

language = "English",

isbn = "0769521711",

pages = "510 -- 513",

booktitle = "Proceedings of the Computer Graphics International Conference",

publisher = "IEEE Computer Society",

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T1 - Combining Sampling and Autoregression for Motion Synthesis

AU - Oziem, DJ

AU - Campbell, NW

AU - Dalton, CJ

AU - Gibson, DP

AU - Thomas, BT

N1 - Conference Organiser: IEEE Computer Society

PY - 2004/6

Y1 - 2004/6

N2 - 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

AB - 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

M3 - Conference Contribution (Conference Proceeding)

SN - 0769521711

SP - 510

EP - 513

BT - Proceedings of the Computer Graphics International Conference

PB - IEEE Computer Society

ER -

Combining Sampling and Autoregression for Motion Synthesis

Abstract

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