Review on Smile Detection

Abstract

Facial expressions are a result of specific movement of face muscles, and these face expressions are considered as a visible sign of a person’s internal thought process, intensions, and internal emotional states. Smile is such a face expression which often indicates, satisfaction, agreement, happiness, etc. Though, a lot of studies have been done over detection of Facial Expression in last decade, smile detection had attracted researcher for more deeper studies. In this review paper, different type of available smile detection so far has been discussed such as Deep Convolutional Neural Network (CNN), Hidden Marcov Model(HMM), K-Nearest Neighbours(KNN), Self Similarity of Gradient(GSS), Histogram of Oriented Gradients (HOG), Gabor-Energy Filters and Local Binary Pattern(LBP) etc and classifier like HAAR Classifier, Hidden Markov Model(HMM), Adaboost Support Vector Machine (SVM),Softmax Classifier and Extreme Learning Machine(ELM).This review paper will prove beneficial for learning about smile detection and its application.