Survey on real‐time facial expression recognition techniques

Abstract

Cameras constantly capture and track facial images and videos on cell phones, webcams etc. In the past decade, facial expression classification and recognition has been the topic of interest as facial expression analysis has a wide range of applications such as intelligent tutoring system, systems for psychological studies etc. This study reviews the latest advances in the algorithms and techniques used in distinct phases of real‐time facial expression recognition. Though there are state‐of‐art approaches to address facial expression identification in real‐time, many issues such as subjectivity‐removal, occlusion, pose, low resolution, scale, variations in illumination level and identification of baseline frame still remain unaddressed. Attempts to deal with such issues for higher accuracy lead to a trade‐off in efficiency. Furthermore, the goal of this study is to elaborate on these issues and highlight the solutions provided by the current approaches. This survey has helped the authors to understand that there is a need for a better strategy to address these issues without having to trade‐off performance in real‐time.

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