Layered Performance Animation with Correlation Maps

dc.contributor.authorNeff, Michaelen_US
dc.contributor.authorAlbrecht, Ireneen_US
dc.contributor.authorSeidel, Hans-Peteren_US
dc.date.accessioned2015-02-21T15:43:25Z
dc.date.available2015-02-21T15:43:25Z
dc.date.issued2007en_US
dc.description.abstractPerformance has a spontaneity and aliveness that can be difficult to capture in more methodical animation processes such as keyframing. Access to performance animation has traditionally been limited to either low degree of freedom characters or required expensive hardware. We present a performance-based animation system for humanoid characters that requires no special hardware, relying only on mouse and keyboard input. We deal with the problem of controlling such a high degree of freedom model with low degree of freedom input through the use of correlation maps which employ 2D mouse input to modify a set of expressively relevant character parameters. Control can be continuously varied by rapidly switching between these maps. We present flexible techniques for varying and combining these maps and a simple process for defining them. The tool is highly configurable, presenting suitable defaults for novices and supporting a high degree of customization and control for experts. Animation can be recorded on a single pass, or multiple layers can be used to increase detail. Results from a user study indicate that novices are able to produce reasonable animations within their first hour of using the system. We also show more complicated results for walking and a standing character that gestures and dances.en_US
dc.description.number3en_US
dc.description.seriesinformationComputer Graphics Forumen_US
dc.description.volume26en_US
dc.identifier.doi10.1111/j.1467-8659.2007.01091.xen_US
dc.identifier.issn1467-8659en_US
dc.identifier.pages675-684en_US
dc.identifier.urihttps://doi.org/10.1111/j.1467-8659.2007.01091.xen_US
dc.publisherThe Eurographics Association and Blackwell Publishing Ltden_US
dc.titleLayered Performance Animation with Correlation Mapsen_US
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