{"id":"https://openalex.org/W7160887609","doi":"https://doi.org/10.48550/arxiv.2605.08753","title":"Simultaneous Monitoring of Shape and Surface Color via 4D Point Clouds: A Registration-free Approach","display_name":"Simultaneous Monitoring of Shape and Surface Color via 4D Point Clouds: A Registration-free Approach","publication_year":2026,"publication_date":"2026-05-09","ids":{"openalex":"https://openalex.org/W7160887609","doi":"https://doi.org/10.48550/arxiv.2605.08753"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.08753","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.08753","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2605.08753","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5120347345","display_name":"Mariafrancesca Patalano","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Patalano, Mariafrancesca","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081439407","display_name":"Giovanna Capizzi","orcid":"https://orcid.org/0000-0002-3187-1365"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Capizzi, Giovanna","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5072570845","display_name":"Kamran Paynabar","orcid":"https://orcid.org/0000-0002-6906-3611"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Paynabar, Kamran","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.3953999876976013,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing 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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.3953999876976013,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing 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/T10638","display_name":"Optical measurement and interference techniques","score":0.1315000057220459,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.06930000334978104,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/preprocessor","display_name":"Preprocessor","score":0.7095000147819519},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.59579998254776},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.526199996471405},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5044999718666077},{"id":"https://openalex.org/keywords/chromatic-scale","display_name":"Chromatic scale","score":0.47760000824928284},{"id":"https://openalex.org/keywords/surface","display_name":"Surface (topology)","score":0.4318999946117401},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.3853999972343445},{"id":"https://openalex.org/keywords/point-distribution-model","display_name":"Point distribution model","score":0.38199999928474426}],"concepts":[{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.7095000147819519},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6492999792098999},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6029999852180481},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.59579998254776},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5737000107765198},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.526199996471405},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5044999718666077},{"id":"https://openalex.org/C196956537","wikidata":"https://www.wikidata.org/wiki/Q202021","display_name":"Chromatic scale","level":2,"score":0.47760000824928284},{"id":"https://openalex.org/C2776799497","wikidata":"https://www.wikidata.org/wiki/Q484298","display_name":"Surface (topology)","level":2,"score":0.4318999946117401},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.3853999972343445},{"id":"https://openalex.org/C118317068","wikidata":"https://www.wikidata.org/wiki/Q2100760","display_name":"Point distribution model","level":2,"score":0.38199999928474426},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.3402999937534332},{"id":"https://openalex.org/C7305733","wikidata":"https://www.wikidata.org/wiki/Q207961","display_name":"Geometric shape","level":2,"score":0.33649998903274536},{"id":"https://openalex.org/C17020691","wikidata":"https://www.wikidata.org/wiki/Q139677","display_name":"Operator (biology)","level":5,"score":0.32919999957084656},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.3280999958515167},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.311599999666214},{"id":"https://openalex.org/C2961294","wikidata":"https://www.wikidata.org/wiki/Q166863","display_name":"Color space","level":3,"score":0.3010999858379364},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.29339998960494995},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.2888000011444092},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2791000008583069},{"id":"https://openalex.org/C2777774050","wikidata":"https://www.wikidata.org/wiki/Q16945110","display_name":"Control point","level":2,"score":0.27309998869895935},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.2718000113964081},{"id":"https://openalex.org/C112604564","wikidata":"https://www.wikidata.org/wiki/Q7489226","display_name":"Shape analysis (program analysis)","level":3,"score":0.26930001378059387},{"id":"https://openalex.org/C152822103","wikidata":"https://www.wikidata.org/wiki/Q7575207","display_name":"Spectral shape analysis","level":3,"score":0.25459998846054077}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.08753","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.08753","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.08753","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.08753","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.46184971928596497}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Advanced":[0],"manufacturing":[1],"technologies":[2],"allow":[3],"for":[4,50,152],"the":[5,77,107,161],"production":[6],"of":[7,20,53,109,165],"intricate":[8],"parts":[9],"featuring":[10],"high":[11],"shape":[12,38,80,93],"complexity":[13],"and":[14,32,39,55,72,76,81,95,111,126,136,163],"spatially-varying":[15],"material":[16,40],"composition.":[17],"Data":[18],"fusion":[19],"point":[21,28,60],"clouds":[22],"with":[23,99],"chromatic":[24],"attributes":[25],"provides":[26],"4D":[27,59],"clouds,":[29],"a":[30,47,100,137],"compact":[31],"informative":[33],"representation":[34],"that":[35,145],"encodes":[36],"both":[37],"information.":[41],"In":[42],"this":[43],"paper,":[44],"we":[45],"present":[46],"registration-free":[48],"framework":[49,64],"Simultaneous":[51],"Monitoring":[52],"shApe":[54],"Color":[56],"(SMAC)":[57],"via":[58],"clouds.":[61],"The":[62],"proposed":[63,89],"leverages":[65],"Laplace-Beltrami":[66],"operator":[67],"spectral":[68],"properties":[69],"to":[70,90,105,159],"capture":[71],"monitor":[73],"geometric":[74],"features":[75],"relationship":[78],"between":[79],"surface":[82],"color.":[83],"A":[84,131],"combined":[85],"monitoring":[86],"scheme":[87],"is":[88],"effectively":[91],"detect":[92],"deformations":[94],"color":[96,113],"anomalies,":[97],"along":[98],"spatially-aware":[101],"post-signal":[102],"diagnostic":[103,157],"procedure":[104],"determine":[106],"source":[108,162],"change":[110],"localize":[112],"anomalies.":[114,166],"Importantly,":[115],"neither":[116],"component":[117],"relies":[118],"on":[119,140],"registration":[120],"or":[121],"mesh":[122],"reconstruction,":[123],"eliminating":[124],"error-prone":[125],"computationally":[127],"expensive":[128],"preprocessing":[129],"steps.":[130],"Monte":[132],"Carlo":[133],"simulation":[134],"study":[135,139],"case":[138],"functionally":[141],"graded":[142],"materials":[143],"demonstrate":[144],"SMAC":[146],"achieves":[147],"effective":[148],"detection":[149],"performance,":[150],"particularly":[151],"subtle":[153],"defects,":[154],"while":[155],"providing":[156],"capabilities":[158],"identify":[160],"location":[164]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-05-13T00:00:00"}
