Infrared Thermal Imaging Face Expression Recognition Based on Harris Algorithm

Abstract

In the field of human–computer interaction, there is a trend toward using emotional interaction and putting emotions at the center. However, traditional facial expression recognition is greatly affected by lighting, skin color and make-up, and is not well recognized. This paper addresses these shortcomings in the following areas: (1) The algorithm of infrared face feature localization is studied, using a combination of region growing algorithm to highlight the organ features of infrared faces, and the Harris corner point detection algorithm to detect the organ features of human beings and locate the location of the large organs related to expressions, such as eyes, nose and mouth. (2) The algorithm for feature extraction is investigated, and the local binarization LBP algorithm is proposed to extract the texture features of the infrared face. The LBP algorithm is synthesized to extract the overall LBP features by applying the innovation of chunking and layering of features. By analyzing and processing the infrared face image data from both visible and infrared face expression data, feature detection, feature extraction and effective classification of the four basic face expressions — happy, angry, disgusted and sad — are performed on the infrared images. The application of the algorithm is processed and improved accordingly to the characteristics of infrared face images, which improves the accuracy of recognition and classification compared to traditional methods.