Human body measurement method
A human body measurement method comprises the following steps that a first material is obtained, and the first material comprises a human body image and a segmentation grid of a human body; a first machine learning model is set, the input of the first machine learning model is the human body image i...
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creator | GUAN YIN YANG XIAOYAN XIAO JINHUA XU GE WANG JIONG TANG WEIMIAN XIAO YONGQIANG |
description | A human body measurement method comprises the following steps that a first material is obtained, and the first material comprises a human body image and a segmentation grid of a human body; a first machine learning model is set, the input of the first machine learning model is the human body image in the first material, the output of the first machine learning model comprises a segmentation grid for the body of the human body in the first material, and the first machine learning model is trained; and through the method, the segmentation grid of the picture can be generated through the first machine learning model, the segmentation result is used as the vector to be more easily used for learning and processing of the second machine learning model, and the final measurement estimation result of the human body parameters can be more accurate.
一种人体测量方法,包括如下步骤,获取第一素材,所述第一素材包括人体图像及对人的身体的分割网格;设置第一机器学习模型,所述第一机器学习模型的输入为第一素材中的人体图像,输出包括第一素材中对人体人的身体的分割网格,训练第一机器学习模型;通过上述方法,我们能够通过第一机器学习模型生成图片的分割网格,通过分割结果作为向量更容易用于第二机器学习模型学习 |
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一种人体测量方法,包括如下步骤,获取第一素材,所述第一素材包括人体图像及对人的身体的分割网格;设置第一机器学习模型,所述第一机器学习模型的输入为第一素材中的人体图像,输出包括第一素材中对人体人的身体的分割网格,训练第一机器学习模型;通过上述方法,我们能够通过第一机器学习模型生成图片的分割网格,通过分割结果作为向量更容易用于第二机器学习模型学习</description><language>chi ; eng</language><subject>CALCULATING ; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS ; COMPUTING ; COUNTING ; IMAGE DATA PROCESSING OR GENERATION, IN GENERAL ; PHYSICS</subject><creationdate>2021</creationdate><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20210518&DB=EPODOC&CC=CN&NR=112819881A$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,780,885,25564,76547</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20210518&DB=EPODOC&CC=CN&NR=112819881A$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>GUAN YIN</creatorcontrib><creatorcontrib>YANG XIAOYAN</creatorcontrib><creatorcontrib>XIAO JINHUA</creatorcontrib><creatorcontrib>XU GE</creatorcontrib><creatorcontrib>WANG JIONG</creatorcontrib><creatorcontrib>TANG WEIMIAN</creatorcontrib><creatorcontrib>XIAO YONGQIANG</creatorcontrib><title>Human body measurement method</title><description>A human body measurement method comprises the following steps that a first material is obtained, and the first material comprises a human body image and a segmentation grid of a human body; a first machine learning model is set, the input of the first machine learning model is the human body image in the first material, the output of the first machine learning model comprises a segmentation grid for the body of the human body in the first material, and the first machine learning model is trained; and through the method, the segmentation grid of the picture can be generated through the first machine learning model, the segmentation result is used as the vector to be more easily used for learning and processing of the second machine learning model, and the final measurement estimation result of the human body parameters can be more accurate.
一种人体测量方法,包括如下步骤,获取第一素材,所述第一素材包括人体图像及对人的身体的分割网格;设置第一机器学习模型,所述第一机器学习模型的输入为第一素材中的人体图像,输出包括第一素材中对人体人的身体的分割网格,训练第一机器学习模型;通过上述方法,我们能够通过第一机器学习模型生成图片的分割网格,通过分割结果作为向量更容易用于第二机器学习模型学习</description><subject>CALCULATING</subject><subject>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</subject><subject>COMPUTING</subject><subject>COUNTING</subject><subject>IMAGE DATA PROCESSING OR GENERATION, IN GENERAL</subject><subject>PHYSICS</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2021</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNrjZJD1KM1NzFNIyk-pVMhNTSwuLUrNTc0rAbJLMvJTeBhY0xJzilN5oTQ3g6Kba4izh25qQX58anFBYnJqXmpJvLOfoaGRhaGlhYWhozExagDSuSRA</recordid><startdate>20210518</startdate><enddate>20210518</enddate><creator>GUAN YIN</creator><creator>YANG XIAOYAN</creator><creator>XIAO JINHUA</creator><creator>XU GE</creator><creator>WANG JIONG</creator><creator>TANG WEIMIAN</creator><creator>XIAO YONGQIANG</creator><scope>EVB</scope></search><sort><creationdate>20210518</creationdate><title>Human body measurement method</title><author>GUAN YIN ; YANG XIAOYAN ; XIAO JINHUA ; XU GE ; WANG JIONG ; TANG WEIMIAN ; XIAO YONGQIANG</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_CN112819881A3</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>chi ; eng</language><creationdate>2021</creationdate><topic>CALCULATING</topic><topic>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</topic><topic>COMPUTING</topic><topic>COUNTING</topic><topic>IMAGE DATA PROCESSING OR GENERATION, IN GENERAL</topic><topic>PHYSICS</topic><toplevel>online_resources</toplevel><creatorcontrib>GUAN YIN</creatorcontrib><creatorcontrib>YANG XIAOYAN</creatorcontrib><creatorcontrib>XIAO JINHUA</creatorcontrib><creatorcontrib>XU GE</creatorcontrib><creatorcontrib>WANG JIONG</creatorcontrib><creatorcontrib>TANG WEIMIAN</creatorcontrib><creatorcontrib>XIAO YONGQIANG</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>GUAN YIN</au><au>YANG XIAOYAN</au><au>XIAO JINHUA</au><au>XU GE</au><au>WANG JIONG</au><au>TANG WEIMIAN</au><au>XIAO YONGQIANG</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>Human body measurement method</title><date>2021-05-18</date><risdate>2021</risdate><abstract>A human body measurement method comprises the following steps that a first material is obtained, and the first material comprises a human body image and a segmentation grid of a human body; a first machine learning model is set, the input of the first machine learning model is the human body image in the first material, the output of the first machine learning model comprises a segmentation grid for the body of the human body in the first material, and the first machine learning model is trained; and through the method, the segmentation grid of the picture can be generated through the first machine learning model, the segmentation result is used as the vector to be more easily used for learning and processing of the second machine learning model, and the final measurement estimation result of the human body parameters can be more accurate.
一种人体测量方法,包括如下步骤,获取第一素材,所述第一素材包括人体图像及对人的身体的分割网格;设置第一机器学习模型,所述第一机器学习模型的输入为第一素材中的人体图像,输出包括第一素材中对人体人的身体的分割网格,训练第一机器学习模型;通过上述方法,我们能够通过第一机器学习模型生成图片的分割网格,通过分割结果作为向量更容易用于第二机器学习模型学习</abstract><oa>free_for_read</oa></addata></record> |
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subjects | CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING IMAGE DATA PROCESSING OR GENERATION, IN GENERAL PHYSICS |
title | Human body measurement method |
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