Facial expression recognition using local binary patterns and discriminant kernel locally linear embedding
نویسندگان
چکیده
منابع مشابه
Facial expression recognition using local binary patterns and discriminant kernel locally linear embedding
Given the nonlinear manifold structure of facial images, a new kernel-based supervised manifold learning algorithm based on locally linear embedding (LLE), called discriminant kernel locally linear embedding (DKLLE), is proposed for facial expression recognition. The proposed DKLLE aims to nonlinearly extract the discriminant information by maximizing the interclass scatter while minimizing the...
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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 ...
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In this work, we propose a novel approach to recognize facial expressions from static images. First, the local binary patterns (LBP) are used to efficiently represent the facial images and then the linear programming (LP) technique is adopted to classify seven facial expressions—anger, disgust, fear, happiness, sadness, surprise, and neutral. Experimental results demonstrate an average recognit...
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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...
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ژورنال
عنوان ژورنال: EURASIP Journal on Advances in Signal Processing
سال: 2012
ISSN: 1687-6180
DOI: 10.1186/1687-6180-2012-20