The thesis deals with editing personal photo archives that are becoming too large to be completely edited by hand. The developed system detects faces and maps them into the space of descriptive embeddings using a deep convolutional neural network. Then, by clustering the embeddings, we determine the identities that the user can edit later. The system was evaluated on two collections of images, one public and one private, we analyzed two clustering methods with the set of parameters. The results represent the basis for further work on the system for automatic organization of photo collections.
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