Perceptual effects of damped and exaggerated facial motion in animated characters

Hyde, Jennifer; Carter, Elizabeth; Kiesler, Sara; Hodgins, Jessica K.

doi:10.1109/fg.2013.6553775

Cited by 24 publications

(22 citation statements)

References 23 publications

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“…In this paper, we examine whether the perceptual effects found in our prior work [20] are applicable when people ac tively interact with an animated avatar rather than passively observe a character. Although we predict that the facial mo tion magnitude of an interactive animated avatar will influ ence participants' judgments, other research suggests that other personality cues may override the effect of facial motion magnitude.…”

Section: Introductionmentioning

confidence: 95%

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Using an Interactive Avatar's Facial Expressiveness to Increase Persuasiveness and Socialness

Hyde

Carter

Kiesler

et al. 2015

Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems

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Research indicates that the facial expressions of animated characters and agents can influence people's perceptions and interactions with these entities. We designed an experiment to examine how an interactive animated avatar's facial ex pressiveness influences dyadic conversations between adults and the avatar. We animated the avatar in realtime using the tracked facial motion of a confederate. To adjust facial ex pressiveness, we damped and exaggerated the avatar's facial motion. We found that ratings of the avatar's extroversion were positively related to its expressiveness. However, im pressions of the avatar's realism and naturalness worsened with increased expressiveness. We also found that the confed erate was more influential when she appeared as the damped or exaggerated avatar. Adjusting the expressiveness of in teractive animated avatars may be a simple way to influence people's social judgments and willingness to collaborate with animated avatars. These results have implications for using avatar facial expressiveness to improve the effectiveness of avatars in various contexts. Adjusting the expressiveness of interactive animated avatars may be a simple way to influence people's social judgments and willingness to collaborate with animated avatars.

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Section: Introductionmentioning

confidence: 95%

“…In a prior experiment using cartoon and comparatively re alistic animated characters [20], we measured viewers' per ceptions of the characters' social traits, such as extrover sion, warmth, and competence. The characters exhibited damped, normal, or exaggerated facial motion while deliv ering a monologue regarding a personal experience.…”

Section: Introductionmentioning

confidence: 99%

Using an Interactive Avatar's Facial Expressiveness to Increase Persuasiveness and Socialness

Hyde

Carter

Kiesler

et al. 2015

Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems

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“…We aimed for our CG characters to be of similar quality. However, previous research has shown that small differences in rendering styles can influence perceptual judgments of CG characters [McDonnell et al 2012;Hyde et al 2013]. SD, the female character, had fewer wrinkles, leading to a smoother face appearance.…”

Section: Discussionmentioning

confidence: 94%

Spatial and Temporal Linearities in Posed and Spontaneous Smiles

Trutoiu

Carter

Pollard

et al. 2014

ACM Trans. Appl. Percept.

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Creating facial animations that convey an animator's intent is a difficult task because animation techniques are necessarily an approximation of the subtle motion of the face. Some animation techniques may result in linearization of the motion of vertices in space (blendshapes, for example), and other, simpler techniques may result in linearization of the motion in time.In this article, we consider the problem of animating smiles and explore how these simplifications in space and time affect the perceived genuineness of smiles. We create realistic animations of spontaneous and posed smiles from high-resolution motion capture data for two computer-generated characters. The motion capture data is processed to linearize the spatial or temporal properties of the original animation. Through perceptual experiments, we evaluate the genuineness of the resulting smiles. Both space and time impact the perceived genuineness. We also investigate the effect of head motion in the perception of smiles and show similar results for the impact of linearization on animations with and without head motion. Our results indicate that spontaneous smiles are more heavily affected by linearizing the spatial and temporal properties than posed smiles. Moreover, the spontaneous smiles were more affected by temporal linearization than spatial linearization. Our results are in accordance with previous research on linearities in facial animation and allow us to conclude that a model of smiles must include a nonlinear model of velocities.

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“…Hyde et al [13] studied the e ects of damped and exaggerated facial motion in virtual characters rendered realistically or in a cartoon style and found that realistically rendered characters bene ted from exaggerated motion and cartoon rendered characters bene ted from damped. In a study by [21], images of illustrated characters showing emotions of fear and anger were manipulated to congruent and incongruent stimuli by exchanging the faces in the images.…”

Section: Related Workmentioning

confidence: 99%

Mimebot—Investigating the Expressibility of Non-Verbal Communication Across Agent Embodiments

Alexanderson

O’Sullivan

Neff

et al. 2017

ACM Trans. Appl. Percept.

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Unlike their human counterparts, arti cial agents such as robots and game characters may be deployed with a large variety of face and body con gurations. Some have articulated bodies but lack facial features, and others may be talking heads ending at the neck. Generally, they have many fewer degrees of freedom than humans through which they must express themselves, and there will inevitably be a ltering e ect when mapping human motion onto the agent. In this paper, we investigate ltering e ects on three types of embodiments, a) an agent with a body but no facial features, b) an agent with a head only and c) an agent with a body and a face. We performed a full performance capture of a mime actor enacting short interactions varying the non-verbal expression along ve dimensions (e.g. level of frustration and level of certainty) for each of the three embodiments. We performed a crowd sourced evaluation experiment comparing the video of the actor to the video of an animated robot for the di erent embodiments and dimensions. Our ndings suggest that the face is especially important to pinpoint emotional reactions, but is also most volatile to ltering e ects. e body motion on the other hand had more diverse interpretations, but tended to preserve the interpretation a er mapping, and thus proved to be more resilient to ltering.

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Perceptual effects of damped and exaggerated facial motion in animated characters

Cited by 24 publications

References 23 publications

Using an Interactive Avatar's Facial Expressiveness to Increase Persuasiveness and Socialness

Using an Interactive Avatar's Facial Expressiveness to Increase Persuasiveness and Socialness

Spatial and Temporal Linearities in Posed and Spontaneous Smiles

Mimebot—Investigating the Expressibility of Non-Verbal Communication Across Agent Embodiments

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