A brief Review of Deep Learning Based Approaches for Facial Expression and Gesture Recognition Based on Visual Information

Abstract

Abstract Psychological researchers and Many Other Researchers have found that body language of a human can provide substantial information in detecting and interpreting emotions. It could express explicit and implicit information mutually of one’s emotional state and intentions over multi-channel modalities. These imperative channels include eye gaze, head movement, facial expression, body posture and gesture and so on. This learning focuses on detecting emotional states from the body language of the hand and face using computer vision and soft computing techniques. The facial expression and gesture recognition have widely used and challenging task in the present scenario. This paper describes brief review of all approaches which are majorly categorized into two -categories where the first category belongs to Conventional approaches and other based on Deep-learning or Non - Conventional. This paper is basically used as a survey of deep-learning approaches for hand-gesture and Facial Expression Recognitions. We describe all review through the taxonomy of deep-learning approaches proposed architecture details, fusion strategies, datasets, way to treat temporal-dimensions of data, its main features, basic knowledge & general understanding of its challenges