Face Recognition System using Hierarchical Pseudo Fisher Matrix

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The increase in available computational power has led to the current widespread use of face recognition and detection systems. It is expected that many applications will be developed including, in particular, those designed to track and identify suspicious persons, which will enhance the functionality of security cameras. This study is concerned with algorithms that address face detection and face recognition, and face organ detection that connects them. We develop face organ detection, face detection, and recognition algorithms that show a high-level performance, as well as robustness against disturbances such as ambient light, referring to the mechanism that humans use to recognize each other. The performance results are presented. In addition, we extend the results of the study to recognition systems for personal behavior.