Fourier principles for emotion-based human figure animation
SIGGRAPH '95 Proceedings of the 22nd annual conference on Computer graphics and interactive techniques
GI '96 Proceedings of the conference on Graphics interface '96
Proceedings of the 27th annual conference on Computer graphics and interactive techniques
The EMOTE model for effort and shape
Proceedings of the 27th annual conference on Computer graphics and interactive techniques
Perceptual metrics for character animation: sensitivity to errors in ballistic motion
ACM SIGGRAPH 2003 Papers
Style translation for human motion
ACM SIGGRAPH 2005 Papers
A data-driven approach to quantifying natural human motion
ACM SIGGRAPH 2005 Papers
Analyzing the physical correctness of interpolated human motion
Proceedings of the 2005 ACM SIGGRAPH/Eurographics symposium on Computer animation
GI '06 Proceedings of Graphics Interface 2006
Cross-cultural differences in recognizing affect from body posture
Interacting with Computers
Evaluating the emotional content of human motions on real and virtual characters
Proceedings of the 5th symposium on Applied perception in graphics and visualization
Person or Puppet? The Role of Stimulus Realism in Attributing Emotion to Static Body Postures
ACII '07 Proceedings of the 2nd international conference on Affective Computing and Intelligent Interaction
Motion Capture and Emotion: Affect Detection in Whole Body Movement
ACII '07 Proceedings of the 2nd international conference on Affective Computing and Intelligent Interaction
Implementing expressive gesture synthesis for embodied conversational agents
GW'05 Proceedings of the 6th international conference on Gesture in Human-Computer Interaction and Simulation
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Motion capture remains a popular and widely-used method for animating virtual characters. However, all practical applications of motion capture rely on motion editing techniques to increase the reusability and flexibility of captured motions. Because humans are proficient in detecting and interpreting subtle details in human motion, understanding the perceptual consequences of motion editing is essential. Thus in this work, we perform three experiments to gain a better understanding of how motion editing might affect the emotional content of a captured performance, particularly changes in posture and dynamics, two factors shown to be important perceptual indicators of bodily emotions. In these studies, we analyse the properties (angles and velocities) and perception (recognition rates and perceived intensities) of a varied set of full-body motion clips representing the six emotions anger, disgust, fear, happiness, sadness, and surprise. We have found that emotions are mostly conveyed through the upper body, that the perceived intensity of an emotion can be reduced by blending with a neutral motion, and that posture changes can alter the perceived emotion but subtle changes in dynamics only alter the intensity.