2,524 research outputs found
EgoFace: Egocentric Face Performance Capture and Videorealistic Reenactment
Face performance capture and reenactment techniques use multiple cameras and sensors, positioned at a distance from the face or mounted on heavy wearable devices. This limits their applications in mobile and outdoor environments. We present EgoFace, a radically new lightweight setup for face performance capture and front-view videorealistic reenactment using a single egocentric RGB camera. Our lightweight setup allows operations in uncontrolled environments, and lends itself to telepresence applications such as video-conferencing from dynamic environments. The input image is projected into a low dimensional latent space of the facial expression parameters. Through careful adversarial training of the parameter-space synthetic rendering, a videorealistic animation is produced. Our problem is challenging as the human visual system is sensitive to the smallest face irregularities that could occur in the final results. This sensitivity is even stronger for video results. Our solution is trained in a pre-processing stage, through a supervised manner without manual annotations. EgoFace captures a wide variety of facial expressions, including mouth movements and asymmetrical expressions. It works under varying illuminations, background, movements, handles people from different ethnicities and can operate in real time
Unsupervised Training for 3D Morphable Model Regression
We present a method for training a regression network from image pixels to 3D
morphable model coordinates using only unlabeled photographs. The training loss
is based on features from a facial recognition network, computed on-the-fly by
rendering the predicted faces with a differentiable renderer. To make training
from features feasible and avoid network fooling effects, we introduce three
objectives: a batch distribution loss that encourages the output distribution
to match the distribution of the morphable model, a loopback loss that ensures
the network can correctly reinterpret its own output, and a multi-view identity
loss that compares the features of the predicted 3D face and the input
photograph from multiple viewing angles. We train a regression network using
these objectives, a set of unlabeled photographs, and the morphable model
itself, and demonstrate state-of-the-art results.Comment: CVPR 2018 version with supplemental material
(http://openaccess.thecvf.com/content_cvpr_2018/html/Genova_Unsupervised_Training_for_CVPR_2018_paper.html
Who am I talking with? A face memory for social robots
In order to provide personalized services and to
develop human-like interaction capabilities robots need to rec-
ognize their human partner. Face recognition has been studied
in the past decade exhaustively in the context of security systems
and with significant progress on huge datasets. However, these
capabilities are not in focus when it comes to social interaction
situations. Humans are able to remember people seen for a
short moment in time and apply this knowledge directly in
their engagement in conversation. In order to equip a robot with
capabilities to recall human interlocutors and to provide user-
aware services, we adopt human-human interaction schemes to
propose a face memory on the basis of active appearance models
integrated with the active memory architecture. This paper
presents the concept of the interactive face memory, the applied
recognition algorithms, and their embedding into the robot’s
system architecture. Performance measures are discussed for
general face databases as well as scenario-specific datasets
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
Smart workplaces: a system proposal for stress management
Over the past last decades of contemporary society, workplaces
have become the primary source of many health issues, leading
to mental problems such as stress, depression, and anxiety.
Among the others, environmental aspects have shown to be the
causes of stress, illness, and lack of productivity. With the arrival
of new technologies, especially in the smart workplaces field,
most studies have focused on investigating the building energy
efficiency models and human thermal comfort. However, little has
been applied to occupants’ stress recognition and well-being
overall. Due to this fact, this present study aims to propose a
stress management solution for an interactive design system that
allows the adapting of comfortable environmental conditions
according to the user preferences by measuring in real-time the
environmental and biological characteristics, thereby helping to
prevent stress, as well as to enable users to cope stress when
being stressed. The secondary objective will focus on evaluating
one part of the system: the mobile application. The proposed
system uses several usability methods to identify users’ needs,
behavior, and expectations from the user-centered design
approach. Applied methods, such as User Research, Card
Sorting, and Expert Review, allowed us to evaluate the design
system according to Heuristics Analysis, resulting in improved
usability of interfaces and experience. The study presents the
research results, the design interface, and usability tests.
According to the User Research results, temperature and noise
are the most common environmental stressors among the users
causing stress and uncomfortable conditions to work in, and the
preference for physical activities over the digital solutions for
coping with stress. Additionally, the System Usability Scale (SUS)
results identified that the system’s usability was measured as
“excellent” and “acceptable” with a final score of 88 points out of
the 100. It is expected that these conclusions can contribute to
future investigations in the smart workplaces study field and their
interaction with the people placed there.Nas últimas décadas da sociedade contemporânea, o local de
trabalho tem se tornado principal fonte de muitos problemas de
saúde mental, como o stress, depressão e ansiedade. Os aspetos
ambientais têm se revelado como as causas de stress, doenças,
falta de produtividade, entre outros. Atualmente, com a chegada de
novas tecnologias, principalmente na área de locais de trabalho
inteligentes, a maioria dos estudos tem se concentrado na
investigação de modelos de eficiência energética de edifícios e
conforto térmico humano. No entanto, pouco foi aplicado ao
reconhecimento do stress dos ocupantes e ao bem-estar geral das
pessoas. Diante disso, o objetivo principal é propor um sistema de
design de gestão do stress para um sistema de design interativo que
permita adaptar as condições ambientais de acordo com as
preferências de utilizador, medindo em tempo real as características
ambientais e biológicas, auxiliando assim na prevenção de stress,
bem como ajuda os utilizadores a lidar com o stress quando estão
sob o mesmo. O segundo objetivo é desenhar e avaliar uma parte
do projeto — o protótipo da aplicação móvel através da realização
de testes de usabilidade. O sistema proposto resulta da abordagem
de design centrado no utilizador, utilizando diversos métodos de
usabilidade para identificar as necessidades, comportamentos e as
expectativas dos utilizadores. Métodos aplicados, como Pesquisa de
Usuário, Card Sorting e Revisão de Especialistas, permitiram avaliar
o sistema de design de acordo com a análise heurística, resultando
numa melhoria na usabilidade das interfaces e experiência. O
estudo apresenta os resultados da pesquisa, a interface do design e
os testes de usabilidade. De acordo com os resultados de User
Research, a temperatura e o ruído são os stressores ambientais
mais comuns entre os utilizadores, causando stresse e condições
menos favoráveis para trabalhar, igualmente existe uma preferência
por atividades físicas sobre as soluções digitais na gestão do
stresse. Adicionalmente, os resultados de System Usability Scale
(SUS) identificaram a usabilidade do sistema de design como
“excelente” e “aceitável” com pontuação final de 88 pontos em 100.
É esperado que essas conclusões possam contribuir para futuras
investigações no campo de estudo dos smart workplaces e sua
interação com os utilizadores
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