Unlock instant, AI-driven research and patent intelligence for your innovation.

A Human Contour Extraction Method Based on Deep Learning

A human contour, deep learning technology, applied in instruments, computing, character and pattern recognition, etc., can solve problems such as poor human contour extraction effect and slow model training speed.

Inactive Publication Date: 2021-04-06
XIAN UNIV OF TECH
View PDF9 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to provide a human body contour extraction method based on deep learning, which solves the problems in the prior art that the human body contour extraction effect in static images is poor and the model training speed is slow

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • A Human Contour Extraction Method Based on Deep Learning
  • A Human Contour Extraction Method Based on Deep Learning
  • A Human Contour Extraction Method Based on Deep Learning

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0163] The source of the data set is the Baidu human body image segmentation database. The data in this database are images containing human bodies taken from various angles. There are 5387 training images and labeled samples in the database. The present invention selects 1000 images among them as the training set, and selects 500 images as the test set in the remaining part. In the experiment, the network input image size is fixed at 224×224. In order to accurately and objectively evaluate the effect of the method in this paper, and to facilitate comparison with existing methods, the overlap rate is used here to measure the performance of the human body contour extraction model of the improved method, where the overlap rate is defined as follows:

[0164]

[0165] Among them, S is the degree of overlap, A P Extracting network-predicted body regions for body contours, A GT for the actual body area. The higher the S, the higher the degree of overlap and the better the ef...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses a human body contour extraction method based on deep learning, which is specifically implemented according to the following steps: step 1, extracting the Gabor texture feature of the original image; step 2, extracting the Canny edge feature of the original image; step 3, building a body suitable for the human body Convolutional neural network architecture for contour extraction; step 4, the original image, the Gabor texture feature map extracted in step 1, and the Canny edge feature map extracted in step 2. are jointly passed into the convolutional neural network constructed in step 3 for training, generating CNN character model; step 5, test the structure of the trained CNN character model to obtain a human body contour image; step 6, record the overlapping rate and time-consuming of the human body contour image through the test process of step 5, and evaluate the human body contour image . The method of the invention achieves higher accuracy rate, improves detection rate and shortens test time.

Description

technical field [0001] The invention belongs to the technical field of machine vision, and in particular relates to a human body contour extraction method based on deep learning. Background technique [0002] Human body contour extraction occupies an important position in the field of computer vision, and is the core technology of human body detection and human behavior recognition. Human contour extraction technology is currently widely used in intelligent monitoring, medical treatment and other fields. The virtual reconstruction of the human body model is the key technology in the modern medical visualization system, and the accurate collection of human body contour information can guarantee the reasonable medical analysis of the patient's disease. On the other hand, with the strengthening of modern society's requirements for personal and public property safety, the utilization rate of intelligent monitoring systems has gradually increased. The primary goal of intelligen...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/00G06K9/46G06K9/62
CPCG06V40/10G06V10/449G06F18/2413
Inventor 王林董楠
Owner XIAN UNIV OF TECH