Style Translation for Human Motion
Name
stf-sig2005-vid.mp4
Size
42.26 MB
Format
Unknown
Checksum (MD5)
8811dc12328c8a204bd1bd85af72ce8e
Author(s)
Hsu, Eugene
Pulli, Kari
Popovic, Jovan
Date Issued
August 1, 2005
Citation
ACM Transactions on Graphics, 24(3):1082-1089, August 2005.
Series/Report no.
Massachusetts Institute of Technology Computer Science and Artificial Intelligence Laboratory
Abstract
Style translation is the process of transforming an input motion into a new style while preserving its original content. This problem is motivated by the needs of interactive applications, which require rapid processing of captured performances. Our solution learns to translate by analyzing differences between performances of the same content in input and output styles. It relies on a novel correspondence algorithm to align motions, and a linear time-invariant model to represent stylistic differences. Once the model is estimated with system identification, our system is capable of translating streaming input with simple linear operations at each frame.
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