Facial Expression Recognition using Principal Component Analysis Combined with Fisher Linear Discriminant Analysis
نویسنده
چکیده
Human facial expressions play an important role in interpersonal relations. This is because humans demonstrate and convey a lot of evident information visually rather than verbally. Although humans recognize facial expressions virtually without effort or delay, reliable expression recognition by machine remains a challenge as of today. To automate recognition of emotional state, machines must be taught to understand facial
منابع مشابه
Facial Expression Recognition Based on Local Binary Patterns and Local Fisher Discriminant Analysis
Automatic facial expression recognition is an interesting and challenging subject in signal processing, pattern recognition, artificial intelligence, etc. In this paper, a new method of facial expression recognition based on local binary patterns (LBP) and local Fisher discriminant analysis (LFDA) is presented. The LBP features are firstly extracted from the original facial expression images. T...
متن کاملFacial expression recognition based on Local Binary Patterns
Classical LBP such as complexity and high dimensions of feature vectors that make it necessary to apply dimension reduction processes. In this paper, we introduce an improved LBP algorithm to solve these problems that utilizes Fast PCA algorithm for reduction of vector dimensions of extracted features. In other words, proffer method (Fast PCA+LBP) is an improved LBP algorithm that is extracted ...
متن کاملFace Recognition
Face recognition has a wide variety of applications such as in identity authentication, access control and surveillance. There has been a lot of research on face recognition over the past few years. They have mainly dealt with different aspects of face recognition. Algorithms have been proposed to recognize faces beyond variations in viewpoint, illumination, pose and expression. This has led to...
متن کاملA Literature review on Facial Expression Recognition Techniques
Automatic facial expression recognition has become a progressive research area since it plays a major role in human-computer-interaction. The facial expression recognition finds major application in areas like social interaction and social intelligence. A review of various techniques used in facial expression recognition like principal component analysis (PCA), linear discriminant analysis (LDA...
متن کاملA shape- and texture-based enhanced Fisher classifier for face recognition
This paper introduces a new face coding and recognition method, the enhanced Fisher classifier (EFC), which employs the enhanced Fisher linear discriminant model (EFM) on integrated shape and texture features. Shape encodes the feature geometry of a face while texture provides a normalized shape-free image. The dimensionalities of the shape and the texture spaces are first reduced using princip...
متن کامل