{"id":"https://openalex.org/W2765772691","doi":"https://doi.org/10.23919/eusipco.2017.8081567","title":"3D laser imaging and sparse points grouping for pavement crack detection","display_name":"3D laser imaging and sparse points grouping for pavement crack detection","publication_year":2017,"publication_date":"2017-08-01","ids":{"openalex":"https://openalex.org/W2765772691","doi":"https://doi.org/10.23919/eusipco.2017.8081567","mag":"2765772691"},"language":"en","primary_location":{"id":"doi:10.23919/eusipco.2017.8081567","is_oa":false,"landing_page_url":"https://doi.org/10.23919/eusipco.2017.8081567","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 25th European Signal Processing Conference (EUSIPCO)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100404067","display_name":"Qingquan Li","orcid":"https://orcid.org/0000-0002-2438-6046"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qingquan Li","raw_affiliation_strings":["4S Lab, Shenzhen University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"4S Lab, Shenzhen University","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101890217","display_name":"Dejin Zhang","orcid":"https://orcid.org/0000-0003-2944-445X"},"institutions":[{"id":"https://openalex.org/I74525822","display_name":"Hubei University of Technology","ror":"https://ror.org/02d3fj342","country_code":"CN","type":"education","lineage":["https://openalex.org/I74525822"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dejin Zhang","raw_affiliation_strings":["EE, Hubei Univ. of Tech"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"EE, Hubei Univ. of Tech","institution_ids":["https://openalex.org/I74525822"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070093927","display_name":"Qin Zou","orcid":"https://orcid.org/0000-0001-7955-0782"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qin Zou","raw_affiliation_strings":["CS, Wuhan University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CS, Wuhan University","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5082565489","display_name":"Hong Lin","orcid":"https://orcid.org/0000-0003-1534-8299"},"institutions":[{"id":"https://openalex.org/I3412056","display_name":"Sanyo (Japan)","ror":"https://ror.org/03wrs2f16","country_code":"JP","type":"company","lineage":["https://openalex.org/I3412056"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Hong Lin","raw_affiliation_strings":["Zoyon Co., Ltd"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zoyon Co., Ltd","institution_ids":["https://openalex.org/I3412056"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":31,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2036","last_page":"2040"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10264","display_name":"Asphalt Pavement Performance Evaluation","score":0.9944000244140625,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10534","display_name":"Structural Health Monitoring Techniques","score":0.9882000088691711,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.8185173273086548},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.6888992190361023},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.5868052244186401},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5510783195495605},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5265474915504456},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.504913866519928},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.44807201623916626},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.44709792733192444},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.33255231380462646},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2481493055820465},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.19568097591400146},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.12372404336929321}],"concepts":[{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.8185173273086548},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.6888992190361023},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.5868052244186401},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5510783195495605},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5265474915504456},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.504913866519928},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.44807201623916626},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.44709792733192444},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.33255231380462646},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2481493055820465},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.19568097591400146},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.12372404336929321},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.23919/eusipco.2017.8081567","is_oa":false,"landing_page_url":"https://doi.org/10.23919/eusipco.2017.8081567","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 25th European Signal Processing Conference (EUSIPCO)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W561485154","https://openalex.org/W1838423138","https://openalex.org/W1977419602","https://openalex.org/W1995130521","https://openalex.org/W2006711847","https://openalex.org/W2083122430","https://openalex.org/W2097500895","https://openalex.org/W2144801789","https://openalex.org/W2166893195","https://openalex.org/W2310487167","https://openalex.org/W2398982639","https://openalex.org/W2402348871","https://openalex.org/W2412799070","https://openalex.org/W2523358814","https://openalex.org/W2560550165","https://openalex.org/W2594490116","https://openalex.org/W6615667905","https://openalex.org/W6638850918","https://openalex.org/W6684323423","https://openalex.org/W6712652987"],"related_works":["https://openalex.org/W4389574804","https://openalex.org/W3016928466","https://openalex.org/W2936725271","https://openalex.org/W3150655618","https://openalex.org/W3108295644","https://openalex.org/W1578717197","https://openalex.org/W2626737336","https://openalex.org/W2005998065","https://openalex.org/W2980582925","https://openalex.org/W3126423817"],"abstract_inverted_index":{"Traditional":[0],"optical":[1],"imaging":[2],"has":[3],"limitations":[4],"in":[5],"capturing":[6],"and":[7,18,37,70,88,131],"representing":[8],"pavement":[9,31],"cracks":[10,47,65],"due":[11],"to":[12,28,45,62,94,121,127,139],"the":[13,30,49,67,74,102,110,128,141,147,150],"impact":[14],"of":[15,73,112,149],"illumination":[16],"variations":[17],"cast":[19],"shadows.":[20],"In":[21],"this":[22],"work,":[23],"laser-imaging":[24],"techniques":[25],"are":[26,83,105,119,137],"employed":[27],"model":[29],"surface":[32],"with":[33],"dense":[34],"3D":[35,50],"points,":[36],"a":[38,89],"sparse":[39],"points":[40],"grouping":[41],"method":[42],"is":[43,60,92],"proposed":[44,151],"detect":[46],"from":[48,66,80],"point":[51,81],"clouds.":[52],"Firstly,":[53],"an":[54],"algorithm":[55,91],"based":[56,135],"on":[57],"frequency":[58],"analysis":[59],"presented":[61],"separate":[63],"potential":[64,113],"control":[68],"profile":[69],"material":[71],"texture":[72],"pavement.":[75],"Secondly,":[76],"range":[77],"images":[78],"generated":[79],"clouds":[82],"partitioned":[84],"into":[85],"image":[86,96],"patches,":[87],"learning":[90],"used":[93],"identify":[95],"patches":[97,104],"probably":[98],"containing":[99],"cracks.":[100,143],"Thirdly,":[101],"extracted":[103],"further":[106],"filtered":[107],"by":[108,125],"checking":[109],"consistency":[111],"crack":[114,122],"directions.":[115],"Finally,":[116],"edge":[117],"weights":[118],"assigned":[120],"seed":[123],"pairs":[124],"referring":[126],"Gestalt":[129],"law,":[130],"minimum":[132],"spanning":[133],"tree":[134],"algorithms":[136],"developed":[138],"extract":[140],"final":[142],"Extensive":[144],"experiments":[145],"demonstrate":[146],"effective":[148],"method.":[152]},"counts_by_year":[{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":7},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":7},{"year":2018,"cited_by_count":3}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}