Automatic generation method of facial beautifying recommendation scheme

Abstract

The invention discloses an automatic generation method of a facial beautifying recommendation scheme. The method mainly comprises the following steps: firstly, acquiring a high-definition face front photo of a user, and inputting the face photo into a face feature parameterization model to obtain face parameterization data of the user; secondly, comparing the user face parameters with the facial features and the five sense organ parameters of the star face in the constructed star face library to obtain the most similar star face and the deformation vector of the five sense organ parameters ofthe user; and inputting the photo and the deformation vector of the user into a face beautifying effect model, and automatically generating a beautifying effect and a quantification scheme corresponding to the user. In the whole process, a user only needs to shoot a high-definition face picture in a matched mode, the whole face beautifying recommendation scheme can be automatically generated, themethod has the advantages of being convenient to operate, short in consumed time and high in precision, and the parameterized data difference before and after facial beautifying and the high-precisionportrait effect after facial beautifying are provided for the user.

Description

technical field [0001] The present invention is based on the research of deep convolutional neural networks, combined with actual business data training to obtain a plurality of deep learning network models, and establishes an artificial intelligence-based method for automatically generating facial plastic surgery recommendation schemes. Background technique [0002] Everyone has a desire for beauty. With the continuous improvement of people's living standards and social acceptance of plastic surgery, body cosmetic surgery has become a common means for people to pursue more beautiful in recent years. Although beauty is subjective, many women hope to objectively and quantitatively evaluate the relevant indicators of their own facial features through certain technical means, so that they can more intuitively see the effect of plastic surgery and the changes in facial facial features parameters. [0003] The existing plastic surgery technology has been improved to a certain ext...

AI Technical Summary

Problems solved by technology

The first reason is that the simulation efficiency of traditional equipment is low, and it takes a long time to measure, which cannot meet the needs of the organization for rapid sales; the second is that the simulation effect is not satisfactory, and the fidelity of the model obtained by scanning is not high

The third is that it cannot meet the user's demand for quantitative index output, and there is no intuitive plastic surgery recommendation plan. The generation of plastic surgery plans mainly relies on the expert experience of plastic surgeons, which has great subjective factors and deviations.

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