Abstract

Faces that move contain rich information about facial form, such as facial features and their configuration, alongside the motion of those features. During social interactions, humans constantly decode and integrate these cues. To fully understand human face perception, it is important to investigate what information dynamic faces convey and how the human visual system extracts and processes information from this visual input. However, partly due to the difficulty of designing well-controlled dynamic face stimuli, many face perception studies still rely on static faces as stimuli. Here, we focus on evidence demonstrating the usefulness of dynamic faces as stimuli, and evaluate different types of dynamic face stimuli to study face perception. Studies based on dynamic face stimuli revealed a high sensitivity of the human visual system to natural facial motion and consistently reported dynamic advantages when static face information is insufficient for the task. These findings support the hypothesis that the human perceptual system integrates sensory cues for robust perception. In the present paper, we review the different types of dynamic face stimuli used in these studies, and assess their usefulness for several research questions. Natural videos of faces are ecological stimuli but provide limited control of facial form and motion. Point-light faces allow for good control of facial motion but are highly unnatural. Image-based morphing is a way to achieve control over facial motion while preserving the natural facial form. Synthetic facial animations allow separation of facial form and motion to study aspects such as identity-from-motion. While synthetic faces are less natural than videos of faces, recent advances in photo-realistic rendering may close this gap and provide naturalistic stimuli with full control over facial motion. We believe that many open questions, such as what dynamic advantages exist beyond emotion and identity recognition and which dynamic aspects drive these advantages, can be addressed adequately with different types of stimuli and will improve our understanding of face perception in more ecological settings.

Highlights

  • Most faces we encounter and interact with move - when we meet a friend, we display continuous facial movements such as nodding, smiling and speaking

  • It seems intuitive to assume that dynamic information would facilitate the identification of facial expressions compared to static images, because expressions develop over time

  • We discuss the usefulness of dynamic faces for face perception studies, review the conditions under which dynamic advantages arise, and compare different kinds of stimuli used to investigate dynamic face processing

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Summary

INTRODUCTION

Most faces we encounter and interact with move - when we meet a friend, we display continuous facial movements such as nodding, smiling and speaking. Humans are sensitive to specific properties of natural motion (e.g., velocity; Pollick et al, 2003; Hill et al, 2005; Bould et al, 2008), to temporal sequencing (e.g., temporal asymmetries in the unfolding of facial expressions; Cunningham and Wallraven, 2009; Reinl and Bartels, 2015; Delis et al, 2016; Korolkova, 2018) and even to perceptual interactions between dynamic facial features (e.g., eye and mouth moving together during yawning; Cook et al, 2015) Given this high sensitivity, what is the additional value of facial motion?

Is There an Added Value of Dynamic Compared to Static Faces?
Perception of Dynamic Face Information Beyond Emotional Expressions
Which Dynamic Aspects Contain Information Beyond Static Face Information?
Advantages and Disadvantages of Different Kinds of Dynamic Face Stimuli
CONCLUSION AND FUTURE DIRECTIONS

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