| Summary: | 碩士 === 國立中興大學 === 資訊科學與工程學系所 === 107 === In the study, the situation of the police investigation case will be simulated. Suppose there is a suspect with only one face photo as a clue. I hope to get 10,000 images to identify the suspect and find the suspect through 10,000 monitors. The face features in the picture will be captured through MTCNN [1] and the suspect will be identified using FaceNet [2].
In the absence of suspected face photos, the face recognition method can only find the most similar photos by calculating the similarity distance by converting two photos into feature vectors. The suspect can be judged with an accuracy of 87% in 200 experiments. Under
the 2000 experiment, the accuracy is 79.2%. When the photo is increased to 10,000, the accuracy drops to 45.1%. In this paper, 2D photo 3D face modeling is implemented by
PRNet [3], and the face images of each angle are incrementally generated through the 3D model, and the classifier is trained to increase the face recognition accuracy from 45.1% to 71.4%.
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