2,524 research outputs found

    EgoFace: Egocentric Face Performance Capture and Videorealistic Reenactment

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    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

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    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

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    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

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    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

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    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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