Proceedings of the 27th annual conference on Computer graphics and interactive techniques
Footskate cleanup for motion capture editing
Proceedings of the 2002 ACM SIGGRAPH/Eurographics symposium on Computer animation
Proceedings of the 29th annual conference on Computer graphics and interactive techniques
Interactive motion generation from examples
Proceedings of the 29th annual conference on Computer graphics and interactive techniques
Interactive control of avatars animated with human motion data
Proceedings of the 29th annual conference on Computer graphics and interactive techniques
Motion capture assisted animation: texturing and synthesis
Proceedings of the 29th annual conference on Computer graphics and interactive techniques
An evaluation of a cost metric for selecting transitions between motion segments
Proceedings of the 2003 ACM SIGGRAPH/Eurographics symposium on Computer animation
Style-based inverse kinematics
ACM SIGGRAPH 2004 Papers
Computing the duration of motion transitions: an empirical approach
SCA '04 Proceedings of the 2004 ACM SIGGRAPH/Eurographics symposium on Computer animation
Robust kinematic constraint detection for motion data
Proceedings of the 2006 ACM SIGGRAPH/Eurographics symposium on Computer animation
Clone attack! Perception of crowd variety
ACM SIGGRAPH 2008 papers
Real-time motion retargeting to highly varied user-created morphologies
ACM SIGGRAPH 2008 papers
Eye-catching crowds: saliency based selective variation
ACM SIGGRAPH 2009 papers
Perceptual evaluation of human animation timewarping
ACM SIGGRAPH ASIA 2010 Sketches
Modeling style and variation in human motion
Proceedings of the 2010 ACM SIGGRAPH/Eurographics Symposium on Computer Animation
Perceiving human motion variety
Proceedings of the ACM SIGGRAPH Symposium on Applied Perception in Graphics and Visualization
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Recent advances in rendering and data-driven animation have enabled the creation of compelling characters with impressive levels of realism. While data-driven techniques can produce animations that are extremely faithful to the original motion, many challenging problems remain because of the high complexity of human motion. A better understanding of the factors that make human motion recognizable and appealing would be of great value in industries where creating a variety of appealing virtual characters with realistic motion is required. To investigate these issues, we captured thirty actors walking, jogging and dancing, and applied their motions to the same virtual character (one each for the males and females). We then conducted a series of perceptual experiments to explore the distinctiveness and attractiveness of these human motions, and whether characteristic motion features transfer across an individual's different gaits. Average faces are perceived to be less distinctive but more attractive, so we explored whether this was also true for body motion. We found that dancing motions were most easily recognized and that distinctiveness in one gait does not predict how recognizable the same actor is when performing a different motion. As hypothesized, average motions were always amongst the least distinctive and most attractive. Furthermore, as 50% of participants in the experiment were Caucasian European and 50% were Asian Korean, we found that the latter were as good as or better at recognizing the motions of the Caucasian actors than their European counterparts, in particular for dancing males, whom they also rated more highly for attractiveness.