2026-04-29T12:21:56Z https://meral.edu.mm/oai

oai:meral.edu.mm:recid/00006635 2021-12-13T00:28:24Z 1582963342780:1605779935331 user-uit

Evaluation of Face Recognition Techniques for Facial Expression Analysis Hla Myat Maw K Zin Lin Myat Thida Mon Face recognition is an important area in the field of biometrics. It has been an active area of research for several decades, but still remains a challenging problem because of the complexity of the human face. Many recognition methods have been proposed, however, most of them are not able to make use of local salient features to effectively capture the face information. Generally, the performance of face recognition system is determined by extracting feature vector exactly and classifying them into a class accurately. Therefore, it is necessary to pay attention to feature extraction method and classifier. In this paper, we compare and analyze the Principle Component Analysis (PCA), Two Dimensional Principle Component Analysis (2DPCA) and Histogram of Oriented Gradients (HOG) based on the recognition rate and access time from the experimental results. The experiment is done on three sets of databases: the AT&T, Yale and own created face database. 2017-11-02 https://meral.edu.mm/records/6635