2,142 research outputs found

    Towards facial mimicry for a virtual human

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    Boukricha H, Wachsmuth I. Towards facial mimicry for a virtual human. In: Reichardt D, ed. Proceedings of the 4th Workshop on Emotion and Computing - Current Research and Future Impact. 2009: 32-39.Mimicking others’ facial expressions is believed to be important in making virtual humans as more natural and believable. As result of an empirical study conducted with a virtual human a large face repertoire of about 6000 faces arranged in Pleasure Arousal Dominance (PAD-) space with respect to two dominance values (dominant vs. submissive) was obtained. Each face in the face repertoire consists of different intensities of the virtual human’s facial muscle actions called Action Units (AUs), modeled following the Facial Action Coding System (FACS). Using this face repertoire an approach towards realizing facial mimicry for a virtual human is topic of this paper. A preliminary evaluation of this first approach is realized with the basic emotions Happy and Angry

    Four not six: revealing culturally common facial expressions of emotion

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    As a highly social species, humans generate complex facial expressions to communicate a diverse range of emotions. Since Darwin’s work, identifying amongst these complex patterns which are common across cultures and which are culture-specific has remained a central question in psychology, anthropology, philosophy, and more recently machine vision and social robotics. Classic approaches to addressing this question typically tested the cross-cultural recognition of theoretically motivated facial expressions representing six emotions, and reported universality. Yet, variable recognition accuracy across cultures suggests a narrower cross-cultural communication, supported by sets of simpler expressive patterns embedded in more complex facial expressions. We explore this hypothesis by modelling the facial expressions of over 60 emotions across two cultures, and segregating out the latent expressive patterns. Using a multi-disciplinary approach, we first map the conceptual organization of a broad spectrum of emotion words by building semantic networks in two cultures. For each emotion word in each culture, we then model and validate its corresponding dynamic facial expression, producing over 60 culturally valid facial expression models. We then apply to the pooled models a multivariate data reduction technique, revealing four latent and culturally common facial expression patterns that each communicates specific combinations of valence, arousal and dominance. We then reveal the face movements that accentuate each latent expressive pattern to create complex facial expressions. Our data questions the widely held view that six facial expression patterns are universal, instead suggesting four latent expressive patterns with direct implications for emotion communication, social psychology, cognitive neuroscience, and social robotics

    From individual characters to large crowds: augmenting the believability of open-world games through exploring social emotion in pedestrian groups

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    Crowds of non-player characters improve the game-play experiences of open-world video-games. Grouping is a common phenomenon of crowds and plays an important role in crowd behaviour. Recent crowd simulation research focuses on group modelling in pedestrian crowds and game-designers have argued that the design of non-player characters should capture and exploit the relationship between characters. The concepts of social groups and inter-character relationships are not new in social psychology, and on-going work addresses the social life of emotions and its behavioural consequences on individuals and groups alike. The aim of this paper is to provide an overview of current research in social psychology, and to use the findings as a source of inspiration to design a social network of non-player characters, with application to the problem of group modelling in simulated crowds in computer games

    An architecture for emotional facial expressions as social signals

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    Simulation of emotional behaviours for virtual agents with personalities

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    We have proposed an improved emotion model based on the well-known PAD model in affective computing and the NEO PI-R personality model in psychology. A novel parameter Emotion Intensity (EI) is proposed to represent different strength of anger, disgust, fear, happiness and sadness. Another novel Resistant formulation is also proposed to effectively simulate the complicated negative emotions. Eight experiments are conducted to simulate different emotional responses under different stimuli with different personality traits

    Simulink toolbox for real-time virtual character control

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    Building virtual humans is a task of formidable complexity. We believe that, especially when building agents that interact with biological humans in real-time over multiple sensorial channels, graphical, data flow oriented programming environments are the development tool of choice. In this paper, we describe a toolbox for the system control and block diagramming environment Simulink that supports the construction of virtual humans. Available blocks include sources for stochastic processes, utilities for coordinate transformation and messaging, as well as modules for controlling gaze and facial expressions

    Affect simulation with primary and secondary emotions

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    Becker-Asano C, Wachsmuth I. Affect simulation with primary and secondary emotions. In: Prendinger H, Lester J, Ishizuka M, eds. Intelligent Virtual Agents. LNCS 5208. Berlin: Springer; 2008: 15-28.In this paper the WASABI Affect Simulation Architecture is introduced, in which a virtual human’s cognitive reasoning capabilities are combined with simulated embodiment to achieve the simulation of primary and secondary emotions. In modeling primary emotions we follow the idea of “Core Affect” in combination with a continuous progression of bodily feeling in three-dimensional emotion space (PAD space), that is only subsequently categorized into discrete emotions. In humans, primary emotions are understood as onto-genetically earlier emotions, which directly influence facial expressions. Secondary emotions, in contrast, afford the ability to reason about current events in the light of experiences and expectations. By technically representing aspects of their connotative meaning in PAD space, we not only assure their mood-congruent elicitation, but also combine them with facial expressions, that are concurrently driven by the primary emotions. An empirical study showed that human players in the Skip-Bo scenario judge our virtual human MAX significantly older when secondary emotions are simulated in addition to primary ones
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