Anticipation from example

Authors:
Victor Zordan;Adriano Macchietto;Jose Medin;Marc Soriano;Chun-Chih Wu;Ronald Metoyer;Robert Rose
Affiliations:
University of California, Riverside;University of California, Riverside;University of California, Riverside;University of California, Riverside;University of California, Riverside;Oregon State University;Oregon State University
Venue:
Proceedings of the 2007 ACM symposium on Virtual reality software and technology
Year:
2007

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Abstract

Automatically generated anticipation is a largely overlooked component of response in character motion for computer animation. We present an approach for generating anticipation to unexpected interactions with examples taken from human motion capture data. Our system generates animation by quickly selecting an anticipatory action using a Support Vector Machine (SVM) which is trained offline to distinguish the characteristics of a given scenario according to a metric that assesses predicted damage and energy expenditure for the character. We show our results for a character that can anticipate by blocking or dodging a threat coming from a variety of locations and targeting any part of the body, from head to toe.