501 research outputs found
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PDE-based Facial Animation: Making the Complex Simple
YesDirect parameterisation is among the most widely used facial animation techniques but requires complicated ways to animate face models which have complex topology. This paper develops a simple solution by introducing a PDE-based facial animation scheme. Using a PDE face model means we only need to animate a group of boundary curves without using any other conventional surface interpolation algorithms. We describe the basis of the method and show results from a practical implementation.EPSR
FacEMOTE: Qualitative Parametric Modifiers for Facial Animations
We propose a control mechanism for facial expressions by applying a few carefully chosen parametric modifications to preexisting expression data streams. This approach applies to any facial animation resource expressed in the general MPEG-4 form, whether taken from a library of preset facial expressions, captured from live performance, or entirely manually created. The MPEG-4 Facial Animation Parameters (FAPs) represent a facial expression as a set of parameterized muscle actions, given as intensity of individual muscle movements over time. Our system varies expressions by changing the intensities and scope of sets of MPEG-4 FAPs. It creates variations in “expressiveness” across the face model rather than simply scale, interpolate, or blend facial mesh node positions. The parameters are adapted from the Effort parameters of Laban Movement Analysis (LMA); we developed a mapping from their values onto sets of FAPs. The FacEMOTE parameters thus perturb a base expression to create a wide range of expressions. Such an approach could allow real-time face animations to change underlying speech or facial expression shapes dynamically according to current agent affect or user interaction needs
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
Towards responsive Sensitive Artificial Listeners
This paper describes work in the recently started project SEMAINE, which aims to build a set of Sensitive Artificial Listeners – conversational agents designed to sustain an interaction with a human user despite limited verbal skills, through robust recognition and generation of non-verbal behaviour in real-time, both when the agent is speaking and listening. We report on data collection and on the design of a system architecture in view of real-time responsiveness
Face modeling and animation language for MPEG-4 XMT framework
This paper proposes FML, an XML-based face modeling and animation language. FML provides a structured content description method for multimedia presentations based on face animation. The language can be used as direct input to compatible players, or be compiled within MPEG-4 XMT framework to create MPEG-4 presentations. The language allows parallel and sequential action description, decision-making and dynamic event-based scenarios, model configuration, and behavioral template definition. Facial actions include talking, expressions, head movements, and low-level MPEG-4 FAPs. The ShowFace and iFACE animation frameworks are also reviewed as example FML-based animation systems
Emotional remapping of music to facial animation
We propose a method to extract the emotional data from a piece
of music and then use that data via a remapping algorithm to
automatically animate an emotional 3D face sequence. The
method is based on studies of the emotional aspect of music and
our parametric-based behavioral head model for face animation.
We address the issue of affective communication remapping in
general, i.e. translation of affective content (eg. emotions, and
mood) from one communication form to another. We report on
the results of our MusicFace system, which use these techniques
to automatically create emotional facial animations from multiinstrument
polyphonic music scores in MIDI format and a
remapping rule set. ? ACM, 2006. This is the author\u27s version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive
version was published in Proceedings of the 2006 ACM SIGGRAPH symposium on Videogames, 143-149. Boston, Massachusetts: ACM. doi:10.1145/1183316.118333
Speech-driven Animation with Meaningful Behaviors
Conversational agents (CAs) play an important role in human computer
interaction. Creating believable movements for CAs is challenging, since the
movements have to be meaningful and natural, reflecting the coupling between
gestures and speech. Studies in the past have mainly relied on rule-based or
data-driven approaches. Rule-based methods focus on creating meaningful
behaviors conveying the underlying message, but the gestures cannot be easily
synchronized with speech. Data-driven approaches, especially speech-driven
models, can capture the relationship between speech and gestures. However, they
create behaviors disregarding the meaning of the message. This study proposes
to bridge the gap between these two approaches overcoming their limitations.
The approach builds a dynamic Bayesian network (DBN), where a discrete variable
is added to constrain the behaviors on the underlying constraint. The study
implements and evaluates the approach with two constraints: discourse functions
and prototypical behaviors. By constraining on the discourse functions (e.g.,
questions), the model learns the characteristic behaviors associated with a
given discourse class learning the rules from the data. By constraining on
prototypical behaviors (e.g., head nods), the approach can be embedded in a
rule-based system as a behavior realizer creating trajectories that are timely
synchronized with speech. The study proposes a DBN structure and a training
approach that (1) models the cause-effect relationship between the constraint
and the gestures, (2) initializes the state configuration models increasing the
range of the generated behaviors, and (3) captures the differences in the
behaviors across constraints by enforcing sparse transitions between shared and
exclusive states per constraint. Objective and subjective evaluations
demonstrate the benefits of the proposed approach over an unconstrained model.Comment: 13 pages, 12 figures, 5 table
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