Facial Detection in Uncontrolled Environments: Systematic Literature Review
ResumoFacial detection is an extremely important topic in biometrics. In particular, its application in uncontrolled environments presents a great challenge for the various existing techniques. This work aims to present and evaluate recent studies on facial detection applied in uncontrolled environments through a systematic review of the literature that addresses what are the main techniques and bases of faces used, as well as what are the main uncontrolled scenarios explored in them. Were formulated three research questions and 85 papers were selected for analysis. Based on the analysis of these works, it can be concluded that the techniques based on convolutional neural networks are the most explored techniques in the literature and that the FDDB face database is the most used in the experiments and specific scenarios present in uncontrolled environments, as occlusion and variation of illumination, are still little investigated.
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