4 research outputs found
Improving Facial Analysis and Performance Driven Animation through Disentangling Identity and Expression
We present techniques for improving performance driven facial animation,
emotion recognition, and facial key-point or landmark prediction using learned
identity invariant representations. Established approaches to these problems
can work well if sufficient examples and labels for a particular identity are
available and factors of variation are highly controlled. However, labeled
examples of facial expressions, emotions and key-points for new individuals are
difficult and costly to obtain. In this paper we improve the ability of
techniques to generalize to new and unseen individuals by explicitly modeling
previously seen variations related to identity and expression. We use a
weakly-supervised approach in which identity labels are used to learn the
different factors of variation linked to identity separately from factors
related to expression. We show how probabilistic modeling of these sources of
variation allows one to learn identity-invariant representations for
expressions which can then be used to identity-normalize various procedures for
facial expression analysis and animation control. We also show how to extend
the widely used techniques of active appearance models and constrained local
models through replacing the underlying point distribution models which are
typically constructed using principal component analysis with
identity-expression factorized representations. We present a wide variety of
experiments in which we consistently improve performance on emotion
recognition, markerless performance-driven facial animation and facial
key-point tracking.Comment: to appear in Image and Vision Computing Journal (IMAVIS
Emotional Silence: Are 3D Animated Female Characters' Emotive Expressions Designed to Fit Stereotypes?
In this thesis, I analyzed the depictions and emotive expressions of female characters by con-ducting a content analysis in two popular contemporary 3D animations. I studied the design of feminine coded appearance and movement using simplified drawings. Based on this study, I claim that female characters and their emotive expressions are still designed to fit stereotypes in contemporary 3D animated children’s movies. My findings are the following:
1. The percentage of female characters in contemporary 3D animated children’s movies is the same as the percentage of females in human society;
2. On the other hand, those female characters did not demonstrate human diversity; and
3. Moreover, their emotions did not demonstrate the diversity of human emotions in terms of how female characters visually express their emotions.
This thesis also establishes a methodology to conduct content analyses on character depiction in 3D animated children’s movies
Emotional Silence: Are 3D Animated Female Characters' Emotive Expressions Designed to Fit Stereotypes?
In this thesis, I analyzed the depictions and emotive expressions of female characters by con-ducting a content analysis in two popular contemporary 3D animations. I studied the design of feminine coded appearance and movement using simplified drawings. Based on this study, I claim that female characters and their emotive expressions are still designed to fit stereotypes in contemporary 3D animated children’s movies. My findings are the following:
1. The percentage of female characters in contemporary 3D animated children’s movies is the same as the percentage of females in human society;
2. On the other hand, those female characters did not demonstrate human diversity; and
3. Moreover, their emotions did not demonstrate the diversity of human emotions in terms of how female characters visually express their emotions.
This thesis also establishes a methodology to conduct content analyses on character depiction in 3D animated children’s movies