| Summary: | This study uses a dataset of unoccluded faces for training to examine the effectiveness of using an eigenface approach to identify faces covered by accessories, particularly sunglasses. The robustness of the eigenface method against partial face occlusion is assessed using principal component analysis, a method often employed in the field of computer vision to perform successful human face detection.
This project intends to show that the suggested face recognition system can correctly identify a person regardless of the presence of accessories, for people who are part of the training set. In contrast, it should be able to classify faces that are absent from the training set as unauthorized with reasonable accuracy.
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