A Survey on Image Acquisition Protocols for Non-posed Facial Expression Recognition Systems

Abstract

Several research methodologies and human face image databases have been developed based on deliberately produced facial expressions of prototypical emotions. However, real-time and spontaneous facial expression recognition cannot be adequately handled by those existing methods and datasets. To address this problem, research efforts have been made to create spontaneous facial expression image datasets as well as to develop algorithms that can process naturally induced affective behavior. This paper introduces these advances and focuses on a small and specific area of spontaneous facial expression recognition. In this paper, we are concentrating on non-posed image acquisition protocols, which strongly influence the subjects for evoking expressions as natural as possible. We categorize the acquisition protocols into four different parts: image acquisition while playing video games, watching emotional videos, during interviews and from other sources. The taxonomy of facial expression acquisition protocols tells about the typical conditions responsible for producing specific facial expressions in that condition. We also address some important design issues related to spontaneous facial expression recognition systems and list the facial expression databases, which are strictly not acted and non-posed. We also put light on the applications of spontaneously evoked facial expression acquisition and recognition because they have potential medical significance. Moreover, we provide a comprehensive analysis and summary of spontaneous facial expression recognition methods by revealing their pros and cons for future researchers.