A Facial Expression Recognition Algorithm based on CNN and LBP Feature

Qintao Xu, Najing Zhao

20202020 IEEE 4th Information Technology, Networking, Electronic and Automation Control Conference (ITNEC)32 citationsDOI

Abstract

In recent years, facial expression recognition technology has been widely used in computer vision, security monitoring and image classification. However, in practical application, it is difficult to solve the rotation problem of facial expression image, which leads to the decrease of expression recognition rate and is difficult to meet the actual demand. Although the convolutional neural network (CNN) can extract the high-dimensional features of the image and has the invariance of gray scale, it does not have the invariance of rotation. Local binary model (LBP) is a feature extraction algorithm with rotation invariance, which can solve the rotation problem to some extent. To solve the above problems, this paper proposes a face expression recognition algorithm based on CNN and LBP, and compares this algorithm with other algorithms. The simulation results show that this algorithm can improve the expression recognition rate under rotation to some extent.

Topics & Concepts

Convolutional neural networkComputer scienceLocal binary patternsRotation (mathematics)Artificial intelligenceFeature extractionFacial expressionPattern recognition (psychology)Facial recognition systemFeature (linguistics)Expression (computer science)Three-dimensional face recognitionFace (sociological concept)AlgorithmFacial expression recognitionImage (mathematics)Computer visionFace detectionHistogramPhilosophyLinguisticsSocial scienceSociologyProgramming languageFace and Expression RecognitionEmotion and Mood RecognitionFace recognition and analysis