Face attractiveness evaluation method based on deep learning

Abstract

The invention discloses a face attractiveness evaluation method based on deep learning. The method comprises the following steps of (1) carrying out map layer decomposition on a face image in a face database and extracting a detail map layer including face skin smoothness information and a brightness map layer including face skin brightness information; (2) under a specifically-designed convolution nerve network structure, taking a detail layer as input training and acquiring one preliminary face attractiveness evaluation network model; (3) taking a brightness layer as input so as to carry out fine-tuning optimization on the network model; (4) taking RGB color information of a face image as the input so as to carry out fine-tuning optimization on the network model and acquiring a final scoring model; and (5) inputting any face image into the scoring model and acquiring a corresponding face attractiveness score. In the invention, a traditional method of manually extracting a face characteristic is abandoned, a convolution nerve network in the deep learning is used to automatically extract the face characteristic and learn a standard of face beauty.

Description

technical field [0001] The invention relates to the research field of computer image data processing and pattern recognition, in particular to a method for evaluating human face attractiveness based on deep learning. Background technique [0002] Heart of beauty in everyone. Everyone wants to be beautiful, but evaluating whether a face image is attractive enough is an abstract problem, which is inevitably affected by the facial image's posture, lighting, race and subjective factors of the judge and so on. However, the evaluation of facial attractiveness is not absolutely abstract. For a long time, researchers have accumulated some quantitative standards on facial attractiveness, such as "three courts and five eyes" and "four highs and three lows" derived from traditional Chinese aesthetic concepts. ", and the "facial golden ratio" that is prevalent in Europe. In recent years, with the rise of artificial intelligence, automated face attractiveness evaluation has also attra...

AI Technical Summary

Problems solved by technology

However, how to let the computer evaluate the attractiveness of human faces objectively is a complex problem. At present, there are relatively few researches at home and abroad in this area. Algorithms for learning based on

However, the work of manually extracting features is not only complicated, but also the selection of appropriate facial features is quite dependent on the experience and knowledge of researchers

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