Method and device for extracting human head image based on deep learning

A technology of deep learning and extraction method, which is applied in the field of human head image extraction based on deep learning, can solve the problems of facial edge fracture and affect the effect of portrait robot portrait, achieve clear edge contour, overcome facial edge fracture, and enrich facial features Effect

Inactive Publication Date: 2018-10-02
深圳市智能机器人研究院
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  • Application Information

AI Technical Summary

Problems solved by technology

These existing detection methods require human participation to adjust the detection results, and pay too much attention to the facial details of th

Method used

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  • Method and device for extracting human head image based on deep learning
  • Method and device for extracting human head image based on deep learning
  • Method and device for extracting human head image based on deep learning

Examples

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Example Embodiment

[0054] Example 1

[0055] A human head image extraction method based on deep learning, such as figure 1 shown, including the following steps:

[0056] S1. Input the picture to be extracted that includes a portrait into a pre-trained YOLO neural network for processing, thereby outputting a head region image, which is a part of the picture to be extracted and includes the head portrait of the portrait;

[0057] S2. Input the head region image into the trained HED neural network for processing, thereby outputting the head edge contour image;

[0058] S3. Input the head area image as the content image and the head edge contour image as the style image to the artistic style transfer neural network for processing, thereby outputting a composite image, and the artistic style transfer neural network is used to transfer the head edge contour image. The style is transferred to the head region image.

[0059] The YOLO neural network used in this embodiment can be trained by the prior ...

Example Embodiment

[0104] Example 2

[0105] In this embodiment, a device for extracting human head images based on deep learning includes:

[0106] a memory for storing at least one program;

[0107] The processor is configured to load the at least one program to execute the deep learning-based human head image extraction method described in Embodiment 1.

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Abstract

The invention discloses a method and device for extracting a human head image based on deep learning. The method comprises the steps of inputting a to-be-extracted picture including a portrait into apre-trained YOLO neural network for processing and outputting a head region image, inputting the head region image into a trained HED neural network for processing and outputting a head edge contour image, inputting the head region image serving as a content image and the head edge contour image serving as a style image into an artistic style transfer neural network for processing, and thus outputting a synthetic image. The device comprises a memory and a processor. The head edge contour image can be extracted from the head region image, and the style of the head edge contour image is transferred to the head region image, thereby realizing the integration of the details such as the head edge contour, the five sense organs and the hairs, and enabling the synthetic image to have rich facialfeatures and clear edge contour. The method and device disclosed by the invention are applied to the technical field of image recognition and processing.

Description

technical field [0001] The present invention relates to the technical field of image recognition processing, in particular to a method and device for extracting human head images based on deep learning. Background technique [0002] Explanation of terms: [0003] YOLO: You Only Look Once, is a target detection method based on deep learning, which can be used to train neural networks. The neural network trained by YOLO can be used to solve the regression problem of target area prediction and category prediction. Its advantage is that it can At the same time, it ensures high detection speed and accuracy; [0004] HED: Holistically-nested Edge Detection, which is embedded in edge detection as a whole, is a deep neural network model. When it is used for image edge contour detection, the input object is a picture, and the output object is the edge contour image of the main shape in the picture. [0005] With the development of robot technology, robots are more and more widely u...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06N3/04
CPCG06V40/10G06V2201/07G06N3/045
Inventor 叶小凤谷也盛卫华
Owner 深圳市智能机器人研究院
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