Cultural dialects of real and synthetic emotional facial expressions

In this article we discuss the aspects of designing facial expressions for virtual humans (VHs) with a specific culture. First we explore the notion of cultures and its relevance for applications with a VH. Then we give a general scheme of designing emotional facial expressions, and identify the stages where a human is involved, either as a real person with some specific role, or as a VH displaying facial expressions. We discuss how the display and the emotional meaning of facial expressions may be measured in objective ways, and how the culture of displayers and the judges may influence the process of analyzing human facial expressions and evaluating synthesized ones. We review psychological experiments on cross-cultural perception of emotional facial expressions. By identifying the culturally critical issues of data collection and interpretation with both real and VHs, we aim at providing a methodological reference and inspiration for further research

A comparison of facial expression properties in five hylobatid species

Little is known about facial communication of lesser apes (family Hylobatidae) and how their facial expressions (and use of) relate to social organization. We investigated facial expressions (defined as combinations of facial movements) in social interactions of mated pairs in five different hylobatid species belonging to three different genera using a recently developed objective coding system, the Facial Action Coding System for hylobatid species (GibbonFACS). We described three important properties of their facial expressions and compared them between genera. First, we compared the rate of facial expressions, which was defined as the number of facial expressions per units of time. Second, we compared their repertoire size, defined as the number of different types of facial expressions used, independent of their frequency. Third, we compared the diversity of expression, defined as the repertoire weighted by the rate of use for each type of facial expression. We observed a higher rate and diversity of facial expression, but no larger repertoire, in Symphalangus (siamangs) compared to Hylobates and Nomascus species. In line with previous research, these results suggest siamangs differ from other hylobatids in certain aspects of their social behavior. To investigate whether differences in facial expressions are linked to hylobatid socio-ecology, we used a Phylogenetic General Least Square (PGLS) regression analysis to correlate those properties with two social factors: group-size and level of monogamy. No relationship between the properties of facial expressions and these socio-ecological factors was found. One explanation could be that facial expressions in hylobatid species are subject to phylogenetic inertia and do not differ sufficiently between species to reveal correlations with factors such as group size and monogamy level. Am. J. Primatol. 76:618-628, 2014

Reverse Engineering Psychologically Valid Facial Expressions of Emotion into Social Robots

Social robots are now part of human society, destined for schools, hospitals, and homes to perform a variety of tasks. To engage their human users, social robots must be equipped with the essential social skill of facial expression communication. Yet, even state-of-the-art social robots are limited in this ability because they often rely on a restricted set of facial expressions derived from theory with well-known limitations such as lacking naturalistic dynamics. With no agreed methodology to objectively engineer a broader variance of more psychologically impactful facial expressions into the social robots' repertoire, human-robot interactions remain restricted. Here, we address this generic challenge with new methodologies that can reverse-engineer dynamic facial expressions into a social robot head. Our data-driven, user-centered approach, which combines human perception with psychophysical methods, produced highly recognizable and human-like dynamic facial expressions of the six classic emotions that generally outperformed state-of-art social robot facial expressions. Our data demonstrates the feasibility of our method applied to social robotics and highlights the benefits of using a data-driven approach that puts human users as central to deriving facial expressions for social robots. We also discuss future work to reverse-engineer a wider range of socially relevant facial expressions including conversational messages (e.g., interest, confusion) and personality traits (e.g., trustworthiness, attractiveness). Together, our results highlight the key role that psychology must continue to play in the design of social robots

Inversion improves the recognition of facial expression in thatcherized images

The Thatcher illusion provides a compelling example of the face inversion effect. However, the marked effect of inversion in the Thatcher illusion contrasts to other studies that report only a small effect of inversion on the recognition of facial expressions. To address this discrepancy, we compared the effects of inversion and thatcherization on the recognition of facial expressions. We found that inversion of normal faces caused only a small reduction in the recognition of facial expressions. In contrast, local inversion of facial features in upright thatcherized faces resulted in a much larger reduction in the recognition of facial expressions. Paradoxically, inversion of thatcherized faces caused a relative increase in the recognition of facial expressions. Together, these results suggest that different processes explain the effects of inversion on the recognition of facial expressions and on the perception of the Thatcher illusion. The grotesque perception of thatcherized images is based on a more orientation-sensitive representation of the face. In contrast, the recognition of facial expression is dependent on a more orientation-insensitive representation. A similar pattern of results was evident when only the mouth or eye region was visible. These findings demonstrate that a key component of the Thatcher illusion is to be found in orientation-specific encoding of the features of the face

Parametric Representations of Facial Expressions on PDE-Based Surfaces

NoParameterisation of facial expressions on PDE surface representations of human faces are presented in this work. Taking advantage of the boundary-value approach inherent to Bloor-Wilson PDE method, facial expressions are achieved by manipulating the original boundary curves. Such curves are responsible for generating a surface representation of a human face in its neutral configuration, so that regions on these curves represent a given facial expression in a fast and realistic manner. Additionally, the parameterisation proposed here is carried out by applying different mathematical transformations to the affected curves according to the corresponding facial expression. Full analytic expressions parameterising some of the most common facial expressions such as smiling and eyebrow raising are in this work. Some graphical examples of these facial expressions are used to illustrate the results obtained using Bloor-Wilson PDE method as the foundations of the parameterisation scheme proposed here. Thus, it is shown that an efficient, intuitive and realistic parameterisation of facial expressions is attainable using Bloor-Wilson PDE method in along with a suitable mathematical expression

Improvements on a simple muscle-based 3D face for realistic facial expressions

Facial expressions play an important role in face-to-face communication. With the development of personal computers capable of rendering high quality graphics, computer facial animation has produced more and more realistic facial expressions to enrich human-computer communication. In this paper, we present a simple muscle-based 3D face model that can produce realistic facial expressions in real time. We extend Waters' (1987) muscle model to generate bulges and wrinkles and to improve the combination of multiple muscle actions. In addition, we present techniques to reduce the computation burden on the muscle mode

Reproducibility of the dynamics of facial expressions in unilateral facial palsy

The aim of this study was to assess the reproducibility of non-verbal facial expressions in unilateral facial paralysis using dynamic four-dimensional (4D) imaging. The Di4D system was used to record five facial expressions of 20 adult patients. The system captured 60 three-dimensional (3D) images per second; each facial expression took 3–4 seconds which was recorded in real time. Thus a set of 180 3D facial images was generated for each expression. The procedure was repeated after 30 min to assess the reproducibility of the expressions. A mathematical facial mesh consisting of thousands of quasi-point ‘vertices’ was conformed to the face in order to determine the morphological characteristics in a comprehensive manner. The vertices were tracked throughout the sequence of the 180 images. Five key 3D facial frames from each sequence of images were analyzed. Comparisons were made between the first and second capture of each facial expression to assess the reproducibility of facial movements. Corresponding images were aligned using partial Procrustes analysis, and the root mean square distance between them was calculated and analyzed statistically (paired Student ttest, P < 0.05). Facial expressions of lip purse, cheek puff, and raising of eyebrows were reproducible. Facial expressions of maximum smile and forceful eye closure were not reproducible. The limited coordination of various groups of facial muscles contributed to the lack of reproducibility of these facial expressions. 4D imaging is a useful clinical tool for the assessment of facial expressions

Dynamic facial expressions of emotion transmit an evolving hierarchy of signals over time

Designed by biological and social evolutionary pressures, facial expressions of emotion comprise specific facial movements to support a near-optimal system of signaling and decoding. Although highly dynamical, little is known about the form and function of facial expression temporal dynamics. Do facial expressions transmit diagnostic signals simultaneously to optimize categorization of the six classic emotions, or sequentially to support a more complex communication system of successive categorizations over time? Our data support the latter. Using a combination of perceptual expectation modeling, information theory, and Bayesian classifiers, we show that dynamic facial expressions of emotion transmit an evolving hierarchy of “biologically basic to socially specific” information over time. Early in the signaling dynamics, facial expressions systematically transmit few, biologically rooted face signals supporting the categorization of fewer elementary categories (e.g., approach/avoidance). Later transmissions comprise more complex signals that support categorization of a larger number of socially specific categories (i.e., the six classic emotions). Here, we show that dynamic facial expressions of emotion provide a sophisticated signaling system, questioning the widely accepted notion that emotion communication is comprised of six basic (i.e., psychologically irreducible) categories, and instead suggesting four