About: Blank expression is a research topic. Over the lifetime, 4 publications have been published within this topic receiving 237 citations. The topic is also known as: straight face & poker face.
TL;DR: A mechanism that enables developers to build virtual characters with dynamic affective facial expressions based on Facial Action Coding is presented and the blends and confusion details of basic emotions are compatible with findings in psychology.
Abstract: Facial emotion expression for virtual characters is used in a wide variety of areas. Often, the primary reason to use emotion expression is not to study emotion expression generation per se, but to use emotion expression in an application or research project. What is then needed is an easy to use and flexible, but also validated mechanism to do so. In this report we present such a mechanism. It enables developers to build virtual characters with dynamic affective facial expressions. The mechanism is based on Facial Action Coding. It is easy to implement, and code is available for download. To show the validity of the expressions generated with the mechanism we tested the recognition accuracy for 6 basic emotions (joy, anger, sadness, surprise, disgust, fear) and 4 blend emotions (enthusiastic, furious, frustrated, and evil). Additionally we investigated the effect of VC distance (z-coordinate), the effect of the VC's face morphology (male vs. female), the effect of a lateral versus a frontal presentation of the expression, and the effect of intensity of the expression. Participants (n=19, Western and Asian subjects) rated the intensity of each expression for each condition (within subject setup) in a non forced choice manner. All of the basic emotions were uniquely perceived as such. Further, the blends and confusion details of basic emotions are compatible with findings in psychology.
TL;DR: This thesis addresses the issue of face representations for facial expression recognition and synthesis using a global appearance model used in conjunction with bilinear factorization allowing to separate expression specifie factors from identity specific factors in the global appearance parameters.
Abstract: Verbal expression fluency and rhetorical ease are incontestable aspects of successful communication. However, humans are able to communicate in a variety of ways besides the use of words, including face gestures and facial expressions. As a matter of fact the idiom "poker face" evokes an attitude of blank expression to prevent detection of intent which suggests that facial expressions constitute an essential modality in human communication. This thesis addresses the issue of face representations for facial expression recognition and synthesis. Ln this context, a global appearance model is used in conjunction with bilinear factorization allowing to separate expression specifie factors from identity specific factors in the global appearance parameters. A feature extraction technique inspired from the above representations is then proposed which consists in automatically computing the optimal identity and expression components that best adapt to an unknown target face. Facial expression recognition and synthesis are finally performed using each representation and their performances are compared quantitatively and qualitatively. Factorization based models yield very interesting synthesis performances in terms of visual quality of the synthetic faces.
TL;DR: A recent conversation with a friend turned to the wonders of GPS and he asked "How could we have ever lived without it?" I agreed and began to explain how GPS worked and how the critical clock correction was done. But I quickly saw a blank expression on my friend's face, and an averting of eyes as discussed by the authors.
Abstract: A recent conversation with a friend turned to the wonders of GPS. "How could we have ever lived without it?" he asked. I agreed, and began to explain how GPS worked and how the critical clock correction was done. But I quickly saw a blank expression on my friend's face, and an averting of eyes.
TL;DR: In this article, a new method was presented for examining effects of emotion in the detection of change in facial expression of emotion, and participants who were induced to feel happiness, sadness, or neutral emotion, saw computerized 100-frame movies in which the first frame always showed a face expressing a specific emotion.