Bridge crack detection and crack three-dimensional visualization method and system
The invention discloses a bridge crack detection and crack three-dimensional visualization method and system, and belongs to the technical field of target detection. A robot is used for carrying out two-dimensional image acquisition on a bridge disease related area to obtain a target detection model...
Gespeichert in:
Hauptverfasser: | , , , , , , , , |
---|---|
Format: | Patent |
Sprache: | chi ; eng |
Schlagworte: | |
Online-Zugang: | Volltext bestellen |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | |
---|---|
container_issue | |
container_start_page | |
container_title | |
container_volume | |
creator | DAI YONGBO REN TAI'AN ZHONG RUXIN XIAO QIANLING HE ZIYI BIAN TAISHAN CAO CHENXI LI BUFAN WEI TIANYI |
description | The invention discloses a bridge crack detection and crack three-dimensional visualization method and system, and belongs to the technical field of target detection. A robot is used for carrying out two-dimensional image acquisition on a bridge disease related area to obtain a target detection model, and the target detection model is primarily extracted based on a YOLOv2 algorithm; target pixel-level segmentation comprises pixel-by-pixel segmentation of a target detection model based on a U-net neural network, and three-dimensional reconstruction comprises building a three-dimensional model by using a erf neural network and a multi-angle two-dimensional image, and adding the target detection model in a pixel-level segmentation stage into the three-dimensional model. According to the invention, the two-dimensional image is utilized to identify the target and establish the three-dimensional model, the target object in the two-dimensional image is marked in the three-dimensional model, the three-dimensional visu |
format | Patent |
fullrecord | <record><control><sourceid>epo_EVB</sourceid><recordid>TN_cdi_epo_espacenet_CN116468683A</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>CN116468683A</sourcerecordid><originalsourceid>FETCH-epo_espacenet_CN116468683A3</originalsourceid><addsrcrecordid>eNrjZAhyKspMSU9VSC5KTM5WSEktSU0uyczPU0jMS4GKlWQUpabqpmTmpuYVA2UScxTKMotLE3MyqxLBKnNTSzLyU8AaiiuLS1JzeRhY0xJzilN5oTQ3g6Kba4izh25qQX58anFBYnJqXmpJvLOfoaGZiZmFmYWxozExagAy5Dh5</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>patent</recordtype></control><display><type>patent</type><title>Bridge crack detection and crack three-dimensional visualization method and system</title><source>esp@cenet</source><creator>DAI YONGBO ; REN TAI'AN ; ZHONG RUXIN ; XIAO QIANLING ; HE ZIYI ; BIAN TAISHAN ; CAO CHENXI ; LI BUFAN ; WEI TIANYI</creator><creatorcontrib>DAI YONGBO ; REN TAI'AN ; ZHONG RUXIN ; XIAO QIANLING ; HE ZIYI ; BIAN TAISHAN ; CAO CHENXI ; LI BUFAN ; WEI TIANYI</creatorcontrib><description>The invention discloses a bridge crack detection and crack three-dimensional visualization method and system, and belongs to the technical field of target detection. A robot is used for carrying out two-dimensional image acquisition on a bridge disease related area to obtain a target detection model, and the target detection model is primarily extracted based on a YOLOv2 algorithm; target pixel-level segmentation comprises pixel-by-pixel segmentation of a target detection model based on a U-net neural network, and three-dimensional reconstruction comprises building a three-dimensional model by using a erf neural network and a multi-angle two-dimensional image, and adding the target detection model in a pixel-level segmentation stage into the three-dimensional model. According to the invention, the two-dimensional image is utilized to identify the target and establish the three-dimensional model, the target object in the two-dimensional image is marked in the three-dimensional model, the three-dimensional visu</description><language>chi ; eng</language><subject>CALCULATING ; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS ; COMPUTING ; COUNTING ; IMAGE DATA PROCESSING OR GENERATION, IN GENERAL ; INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIRCHEMICAL OR PHYSICAL PROPERTIES ; MEASURING ; PHYSICS ; TESTING</subject><creationdate>2023</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=20230721&DB=EPODOC&CC=CN&NR=116468683A$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,780,885,25563,76318</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20230721&DB=EPODOC&CC=CN&NR=116468683A$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>DAI YONGBO</creatorcontrib><creatorcontrib>REN TAI'AN</creatorcontrib><creatorcontrib>ZHONG RUXIN</creatorcontrib><creatorcontrib>XIAO QIANLING</creatorcontrib><creatorcontrib>HE ZIYI</creatorcontrib><creatorcontrib>BIAN TAISHAN</creatorcontrib><creatorcontrib>CAO CHENXI</creatorcontrib><creatorcontrib>LI BUFAN</creatorcontrib><creatorcontrib>WEI TIANYI</creatorcontrib><title>Bridge crack detection and crack three-dimensional visualization method and system</title><description>The invention discloses a bridge crack detection and crack three-dimensional visualization method and system, and belongs to the technical field of target detection. A robot is used for carrying out two-dimensional image acquisition on a bridge disease related area to obtain a target detection model, and the target detection model is primarily extracted based on a YOLOv2 algorithm; target pixel-level segmentation comprises pixel-by-pixel segmentation of a target detection model based on a U-net neural network, and three-dimensional reconstruction comprises building a three-dimensional model by using a erf neural network and a multi-angle two-dimensional image, and adding the target detection model in a pixel-level segmentation stage into the three-dimensional model. According to the invention, the two-dimensional image is utilized to identify the target and establish the three-dimensional model, the target object in the two-dimensional image is marked in the three-dimensional model, the three-dimensional visu</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>INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIRCHEMICAL OR PHYSICAL PROPERTIES</subject><subject>MEASURING</subject><subject>PHYSICS</subject><subject>TESTING</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2023</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNrjZAhyKspMSU9VSC5KTM5WSEktSU0uyczPU0jMS4GKlWQUpabqpmTmpuYVA2UScxTKMotLE3MyqxLBKnNTSzLyU8AaiiuLS1JzeRhY0xJzilN5oTQ3g6Kba4izh25qQX58anFBYnJqXmpJvLOfoaGZiZmFmYWxozExagAy5Dh5</recordid><startdate>20230721</startdate><enddate>20230721</enddate><creator>DAI YONGBO</creator><creator>REN TAI'AN</creator><creator>ZHONG RUXIN</creator><creator>XIAO QIANLING</creator><creator>HE ZIYI</creator><creator>BIAN TAISHAN</creator><creator>CAO CHENXI</creator><creator>LI BUFAN</creator><creator>WEI TIANYI</creator><scope>EVB</scope></search><sort><creationdate>20230721</creationdate><title>Bridge crack detection and crack three-dimensional visualization method and system</title><author>DAI YONGBO ; REN TAI'AN ; ZHONG RUXIN ; XIAO QIANLING ; HE ZIYI ; BIAN TAISHAN ; CAO CHENXI ; LI BUFAN ; WEI TIANYI</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_CN116468683A3</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>chi ; eng</language><creationdate>2023</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>INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIRCHEMICAL OR PHYSICAL PROPERTIES</topic><topic>MEASURING</topic><topic>PHYSICS</topic><topic>TESTING</topic><toplevel>online_resources</toplevel><creatorcontrib>DAI YONGBO</creatorcontrib><creatorcontrib>REN TAI'AN</creatorcontrib><creatorcontrib>ZHONG RUXIN</creatorcontrib><creatorcontrib>XIAO QIANLING</creatorcontrib><creatorcontrib>HE ZIYI</creatorcontrib><creatorcontrib>BIAN TAISHAN</creatorcontrib><creatorcontrib>CAO CHENXI</creatorcontrib><creatorcontrib>LI BUFAN</creatorcontrib><creatorcontrib>WEI TIANYI</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>DAI YONGBO</au><au>REN TAI'AN</au><au>ZHONG RUXIN</au><au>XIAO QIANLING</au><au>HE ZIYI</au><au>BIAN TAISHAN</au><au>CAO CHENXI</au><au>LI BUFAN</au><au>WEI TIANYI</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>Bridge crack detection and crack three-dimensional visualization method and system</title><date>2023-07-21</date><risdate>2023</risdate><abstract>The invention discloses a bridge crack detection and crack three-dimensional visualization method and system, and belongs to the technical field of target detection. A robot is used for carrying out two-dimensional image acquisition on a bridge disease related area to obtain a target detection model, and the target detection model is primarily extracted based on a YOLOv2 algorithm; target pixel-level segmentation comprises pixel-by-pixel segmentation of a target detection model based on a U-net neural network, and three-dimensional reconstruction comprises building a three-dimensional model by using a erf neural network and a multi-angle two-dimensional image, and adding the target detection model in a pixel-level segmentation stage into the three-dimensional model. According to the invention, the two-dimensional image is utilized to identify the target and establish the three-dimensional model, the target object in the two-dimensional image is marked in the three-dimensional model, the three-dimensional visu</abstract><oa>free_for_read</oa></addata></record> |
fulltext | fulltext_linktorsrc |
identifier | |
ispartof | |
issn | |
language | chi ; eng |
recordid | cdi_epo_espacenet_CN116468683A |
source | esp@cenet |
subjects | CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING IMAGE DATA PROCESSING OR GENERATION, IN GENERAL INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIRCHEMICAL OR PHYSICAL PROPERTIES MEASURING PHYSICS TESTING |
title | Bridge crack detection and crack three-dimensional visualization method and system |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-13T01%3A12%3A33IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-epo_EVB&rft_val_fmt=info:ofi/fmt:kev:mtx:patent&rft.genre=patent&rft.au=DAI%20YONGBO&rft.date=2023-07-21&rft_id=info:doi/&rft_dat=%3Cepo_EVB%3ECN116468683A%3C/epo_EVB%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rfr_iscdi=true |