2,734 research outputs found
Dynamic Facial Expression of Emotion Made Easy
Facial emotion expression for virtual characters is used in a wide variety of
areas. Often, the primary reason to use emotion expression is not to study
emotion expression generation per se, but to use emotion expression in an
application or research project. What is then needed is an easy to use and
flexible, but also validated mechanism to do so. In this report we present such
a mechanism. It enables developers to build virtual characters with dynamic
affective facial expressions. The mechanism is based on Facial Action Coding.
It is easy to implement, and code is available for download. To show the
validity of the expressions generated with the mechanism we tested the
recognition accuracy for 6 basic emotions (joy, anger, sadness, surprise,
disgust, fear) and 4 blend emotions (enthusiastic, furious, frustrated, and
evil). Additionally we investigated the effect of VC distance (z-coordinate),
the effect of the VC's face morphology (male vs. female), the effect of a
lateral versus a frontal presentation of the expression, and the effect of
intensity of the expression. Participants (n=19, Western and Asian subjects)
rated the intensity of each expression for each condition (within subject
setup) in a non forced choice manner. All of the basic emotions were uniquely
perceived as such. Further, the blends and confusion details of basic emotions
are compatible with findings in psychology
On Face Segmentation, Face Swapping, and Face Perception
We show that even when face images are unconstrained and arbitrarily paired,
face swapping between them is actually quite simple. To this end, we make the
following contributions. (a) Instead of tailoring systems for face
segmentation, as others previously proposed, we show that a standard fully
convolutional network (FCN) can achieve remarkably fast and accurate
segmentations, provided that it is trained on a rich enough example set. For
this purpose, we describe novel data collection and generation routines which
provide challenging segmented face examples. (b) We use our segmentations to
enable robust face swapping under unprecedented conditions. (c) Unlike previous
work, our swapping is robust enough to allow for extensive quantitative tests.
To this end, we use the Labeled Faces in the Wild (LFW) benchmark and measure
the effect of intra- and inter-subject face swapping on recognition. We show
that our intra-subject swapped faces remain as recognizable as their sources,
testifying to the effectiveness of our method. In line with well known
perceptual studies, we show that better face swapping produces less
recognizable inter-subject results. This is the first time this effect was
quantitatively demonstrated for machine vision systems
Creative tools for producing realistic 3D facial expressions and animation
Creative exploration of realistic 3D facial animation is a popular but very challenging task due to the high level knowledge and skills required. This forms a barrier for creative individuals who have limited technical skills but wish to explore their creativity in this area. This paper proposes a new technique that facilitates users’ creative exploration by hiding the technical complexities of producing facial expressions and animation. The proposed technique draws on research from psychology, anatomy and employs Autodesk Maya as a use case by developing a creative tool, which extends Maya’s Blend Shape Editor. User testing revealed that novice users in the creative media, employing the proposed tool can produce rich and realistic facial expressions that portray new interesting emotions. It reduced production time by 25% when compared to Maya and by 40% when compared to 3DS Max equivalent tools
Multispace behavioral model for face-based affective social agents
This paper describes a behavioral model for affective social agents based on three independent but interacting parameter spaces:
knowledge, personality, andmood. These spaces control a lower-level geometry space that provides parameters at the facial feature
level. Personality and mood use findings in behavioral psychology to relate the perception of personality types and emotional
states to the facial actions and expressions through two-dimensional models for personality and emotion. Knowledge encapsulates
the tasks to be performed and the decision-making process using a specially designed XML-based language. While the geometry
space provides an MPEG-4 compatible set of parameters for low-level control, the behavioral extensions available through the
triple spaces provide flexible means of designing complicated personality types, facial expression, and dynamic interactive scenarios
Lip syncing method for realistic expressive 3D face model
Lip synchronization of 3D face model is now being used in a multitude of important fields. It brings a more human, social and dramatic reality to computer games, films and interactive multimedia, and is growing in use and importance. High level of realism can be used in demanding applications such as computer games and cinema. Authoring lip syncing with complex and subtle expressions is still difficult and fraught with problems in terms of realism. This research proposed a lip syncing method of realistic expressive 3D face model. Animated lips requires a 3D face model capable of representing the myriad shapes the human face experiences during speech and a method to produce the correct lip shape at the correct time. The paper presented a 3D face model designed to support lip syncing that align with input audio file. It deforms using Raised Cosine Deformation (RCD) function that is grafted onto the input facial geometry. The face model was based on MPEG-4 Facial Animation (FA) Standard. This paper proposed a method to animate the 3D face model over time to create animated lip syncing using a canonical set of visemes for all pairwise combinations of a reduced phoneme set called ProPhone. The proposed research integrated emotions by the consideration of Ekman model and Plutchik’s wheel with emotive eye movements by implementing Emotional Eye Movements Markup Language (EEMML) to produce realistic 3D face model. © 2017 Springer Science+Business Media New Yor
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