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National Repository of Grey Literature 2 records found  Search took 0.00 seconds. 
Extraction of Face Covered by a Mask
 Križka, Dominik ; Tinka, Jan (referee) ; Drahanský, Martin (advisor)
The bachelor thesis focuses on numerous techniques of extraction of a face covered by a mask, with assistance of the terahertz and infrared radiation. In order to resolve the issue, a database with photos of twelve people was created with various levels of face cover. The face extraction is then attempted with three techniques. First method uses ORB and SIFT descriptors on the face recognition. Descriptors were unable to successfully extract the masked face. The second technique is utilizes a facial landmark predictor. During the recognition of an unmasked face, the predictor is able to correctly represent regions of the face. With increased levels of coverage on face, it gets progressively more difficult to find facial landmarks correctly and inaccuracies occur. The last approach encodes the faces to numeric format and compares them between each other. The success rate of the extraction depends primarily on the quality of the model, which was trained on the neural network principle. The main contribution of the bachelor thesis, lies in the carried out experiments. In some cases of experiments, the identity of faces covered by scarf or balaclava were successfully revealed with usage of the infrared radiation and face encoding technique.
Detailed record
Extraction of Face Covered by a Mask
 Križka, Dominik ; Tinka, Jan (referee) ; Drahanský, Martin (advisor)
The bachelor thesis focuses on numerous techniques of extraction of a face covered by a mask, with assistance of the terahertz and infrared radiation. In order to resolve the issue, a database with photos of twelve people was created with various levels of face cover. The face extraction is then attempted with three techniques. First method uses ORB and SIFT descriptors on the face recognition. Descriptors were unable to successfully extract the masked face. The second technique is utilizes a facial landmark predictor. During the recognition of an unmasked face, the predictor is able to correctly represent regions of the face. With increased levels of coverage on face, it gets progressively more difficult to find facial landmarks correctly and inaccuracies occur. The last approach encodes the faces to numeric format and compares them between each other. The success rate of the extraction depends primarily on the quality of the model, which was trained on the neural network principle. The main contribution of the bachelor thesis, lies in the carried out experiments. In some cases of experiments, the identity of faces covered by scarf or balaclava were successfully revealed with usage of the infrared radiation and face encoding technique.
Detailed record

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