12,114 research outputs found
A Mimetic Strategy to Engage Voluntary Physical Activity In Interactive Entertainment
We describe the design and implementation of a vision based interactive
entertainment system that makes use of both involuntary and voluntary control
paradigms. Unintentional input to the system from a potential viewer is used to
drive attention-getting output and encourage the transition to voluntary
interactive behaviour. The iMime system consists of a character animation
engine based on the interaction metaphor of a mime performer that simulates
non-verbal communication strategies, without spoken dialogue, to capture and
hold the attention of a viewer. The system was developed in the context of a
project studying care of dementia sufferers. Care for a dementia sufferer can
place unreasonable demands on the time and attentional resources of their
caregivers or family members. Our study contributes to the eventual development
of a system aimed at providing relief to dementia caregivers, while at the same
time serving as a source of pleasant interactive entertainment for viewers. The
work reported here is also aimed at a more general study of the design of
interactive entertainment systems involving a mixture of voluntary and
involuntary control.Comment: 6 pages, 7 figures, ECAG08 worksho
3D Face tracking and gaze estimation using a monocular camera
Estimating a user’s gaze direction, one of the main novel user interaction technologies, will eventually be used for numerous applications where current methods are becoming less effective. In this paper, a new method is presented for estimating the gaze direction using Canonical Correlation Analysis (CCA), which finds a linear relationship between two datasets defining the face pose and the corresponding facial appearance changes. Afterwards, iris tracking is performed by blob detection using a 4-connected component labeling algorithm. Finally, a gaze vector is calculated based on gathered eye properties. Results obtained from datasets and real-time input confirm the robustness of this metho
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
A motion system for social and animated robots
This paper presents an innovative motion system that is used to control the motions and animations of a social robot. The social robot Probo is used to study Human-Robot Interactions (HRI), with a special focus on Robot Assisted Therapy (RAT). When used for therapy it is important that a social robot is able to create an "illusion of life" so as to become a believable character that can communicate with humans. The design of the motion system in this paper is based on insights from the animation industry. It combines operator-controlled animations with low-level autonomous reactions such as attention and emotional state. The motion system has a Combination Engine, which combines motion commands that are triggered by a human operator with motions that originate from different units of the cognitive control architecture of the robot. This results in an interactive robot that seems alive and has a certain degree of "likeability". The Godspeed Questionnaire Series is used to evaluate the animacy and likeability of the robot in China, Romania and Belgium
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 combining the facial movements of a talking head
We present work on Obie, an embodied conversational
agent framework. An embodied conversational agent, or
talking head, consists of three main components. The
graphical part consists of a face model and a facial muscle
model. Besides the graphical part, we have implemented
an emotion model and a mapping from emotions to facial
expressions. The animation part of the framework focuses
on the combination of different facial movements
temporally. In this paper we propose a scheme of
combining facial movements on a 3D talking head
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