Virtual manicure try-on method based on deep learning

A technology of deep learning and manicure, applied in the field of virtual manicure, can solve the problems that users cannot obtain the display effect of manicure plan, and achieve the effect of low price, easy to use and manage, and safe implementation method

Pending Publication Date: 2020-04-21
SHANGHAI UNIV OF MEDICINE & HEALTH SCI
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, this method can only be done in places where nail art machines are installed, and the lighting source provided by the nail art mac

Method used

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  • Virtual manicure try-on method based on deep learning
  • Virtual manicure try-on method based on deep learning
  • Virtual manicure try-on method based on deep learning

Examples

Experimental program
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Example Embodiment

[0028] Example

[0029] Such as figure 1 As shown, the nail image segmentation method based on the deep full convolutional neural network provided by the present invention first inputs the digital image containing the nail area, uses the trained deep full convolutional neural network to predict the pixels in the input image, and finally The segmentation result of the nail area is obtained; after the segmentation result is obtained, the system uses the color and texture information contained in the nail art scheme selected by the user to recolor the nail area in the original image to achieve the purpose of virtual nail art.

[0030] The deep full convolutional neural network accepts the original image containing nails as input, and obtains the segmentation result of the nail area through the processing of the neural network; using the obtained segmentation area as a mask, the nail area of ​​the input image is adjusted according to the coloring scheme preferred by the customer Refill...

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Abstract

The invention relates to a virtual manicure try-on method based on deep learning, and the method comprises the steps: obtaining a single image or video image containing a nail, employing a deep learning full convolution neural network method to segment and track a nail region in real time, combining with the color of the nail selected by a user and the re-coloring of a pattern template, and achieving the virtual manicure try-on function. Compared with the prior art, the method has the advantages that the deep learning and virtual reality technologies are adopted, the shot single picture or continuous video images containing the nails are processed, the nails are segmented and tracked in real time, and the function of virtual manicure try-on is achieved in combination with the selected templates such as the colors/patterns of the nails. According to the method, through the form of a mobile phone APP, customers are not limited by places and equipment, manicure try-on and selection are completed, and the experience feeling of the customers is enhanced.

Description

technical field [0001] The present invention relates to a virtual manicure method, in particular to a virtual manicure try-on method based on deep learning. Background technique [0002] With the improvement of living standards, people are turning more from material life needs to spiritual needs, and beautifying finger (toe) nails is just a manifestation of this. Manicure has become a trend, which is to recolor or decorate individual fingernails or toenails (the following are only expressed with nails as an example) according to personal hand shape, nail shape, skin color, clothing color and subjective feelings to form various logos Personalized nail texture patterns satisfy personal pursuit of beautiful image. [0003] Manicure is a complex process, including program selection, disinfection, cleaning, nursing, maintenance and beautification. Among them, the selection of the nail art plan determines the follow-up work process, which is particularly important. In order to ...

Claims

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Application Information

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IPC IPC(8): G06K9/62G06K9/34G06N3/04G06N3/08G06Q30/06
CPCG06N3/08G06Q30/0621G06V10/267G06N3/045G06F18/241
Inventor 孙九爱王超楠刘小瑾王雄魏玲吴忠航
Owner SHANGHAI UNIV OF MEDICINE & HEALTH SCI
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