Visible to the public A Novel Hybrid Pyramid Texture-Based Facial Expression Recognition

TitleA Novel Hybrid Pyramid Texture-Based Facial Expression Recognition
Publication TypeConference Paper
Year of Publication2021
AuthorsFallah, Zahra, Ebrahimpour-Komleh, Hossein, Mousavirad, Seyed Jalaleddin
Conference Name2021 5th International Conference on Pattern Recognition and Image Analysis (IPRIA)
Keywordsclassifier, Databases, face recognition, facial expression recognition, facial recognition, frequency-domain analysis, Gaussian filter, Human Behavior, Image analysis, image recognition, local binary pattern, local phase quantization, Metrics, pubcrawl, pyramid images, Quantization (signal), resilience, Resiliency, Transforms
AbstractAutomated analysis of facial expressions is one of the most interesting and challenging problems in many areas such as human-computer interaction. Facial images are affected by many factors, such as intensity, pose and facial expressions. These factors make facial expression recognition problem a challenge. The aim of this paper is to propose a new method based on the pyramid local binary pattern (PLBP) and the pyramid local phase quantization (PLPQ), which are the extension of the local binary pattern (LBP) and the local phase quantization (LPQ) as two methods for extracting texture features. LBP operator is used to extract LBP feature in the spatial domain and LPQ operator is used to extract LPQ feature in the frequency domain. The combination of features in spatial and frequency domains can provide important information in both domains. In this paper, PLBP and PLPQ operators are separately used to extract features. Then, these features are combined to create a new feature vector. The advantage of pyramid transform domain is that it can recognize facial expressions efficiently and with high accuracy even for very low-resolution facial images. The proposed method is verified on the CK+ facial expression database. The proposed method achieves the recognition rate of 99.85% on CK+ database.
DOI10.1109/IPRIA53572.2021.9483475
Citation Keyfallah_novel_2021