Face skin type analysis method and system based on depth learning and generation confrontation network

Abstract

The invention provides a face skin type analysis method and system based on depth learning and the generation confrontation network. The method comprises steps that the image acquisition step, a to-be-analyzed face image is acquired; the block division step, the to-be-analyzed face image is analyzed, and skin blocks of the to-be-analyzed face image are divided according to organs; the analysis step, different skin analyzers are inputted to different skin blocks and are used for analyzing skin states of the corresponding skin blocks; and the result output step, the analysis results of all the skin analyzers are outputted. The method is advantaged in that on the condition that face skin type data is not easy to acquire and distribution is free, through the generation confrontation network, auxiliary data is generated, a depth learning model is utilized to replace a traditional image processing algorithm for skin type analysis application, face skin details can be analyzed, in combination with the generation confrontation network, for different-characteristic skins, the limited data is utilized to generate training data, and the better training effect is acquired.

Description

technical field [0001] The invention belongs to the technical field of image processing, and in particular relates to a face and skin quality analysis method and system based on deep learning and generative confrontation networks. Background technique [0002] In the past few decades, there have been many related researches on deep learning, but due to the huge amount of training data required, many of them cannot be realized. In recent years, due to the development of big data and the Internet, researchers can obtain a large amount of training data, so deep learning technology has begun to develop rapidly. With the popularity of live broadcasts and short videos, commercial applications of facial effects and editing have received a lot of attention and research data. [0003] However, the current research on face analysis seldom analyzes skin details. Because face and skin data are relatively private and involve medical behavior, the data is not easy to obtain. In the past,...

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Problems solved by technology

[0003] However, the current research on face analysis seldom analyzes skin details. Because face and skin data are relatively private and involve medical behavior, the data is not easy to obtain. In the past, traditional image processing techniques that do not require a large amount of data are mostly used. The effect is limited, so how to use deep learning to analyze human face skin under limited data has become an important research topic

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