{"id":"https://openalex.org/W7129201289","doi":"https://doi.org/10.48550/arxiv.2602.14376","title":"Event-based Visual Deformation Measurement","display_name":"Event-based Visual Deformation Measurement","publication_year":2026,"publication_date":"2026-02-16","ids":{"openalex":"https://openalex.org/W7129201289","doi":"https://doi.org/10.48550/arxiv.2602.14376"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2602.14376","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.14376","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2602.14376","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5126207068","display_name":"Yuliang Wu","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Wu, Yuliang","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126186059","display_name":"Wei Zhai","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhai, Wei","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084455146","display_name":"Yuxin Cui","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cui, Yuxin","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126210298","display_name":"Tiesong Zhao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhao, Tiesong","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126261155","display_name":"Yang Cao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cao, Yang","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5126246879","display_name":"Zheng-Jun Zha","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zha, Zheng-Jun","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5126207068"],"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/T10531","display_name":"Advanced Vision and Imaging","score":0.4350999891757965,"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"}},"topics":[{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":0.4350999891757965,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.14380000531673431,"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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.13339999318122864,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/benchmark","display_name":"Benchmark (surveying)","score":0.49070000648498535},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.475600004196167},{"id":"https://openalex.org/keywords/deformation","display_name":"Deformation (meteorology)","score":0.46149998903274536},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.4115999937057495},{"id":"https://openalex.org/keywords/affine-transformation","display_name":"Affine transformation","score":0.399399995803833},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.39079999923706055},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.38429999351501465},{"id":"https://openalex.org/keywords/structure-from-motion","display_name":"Structure from motion","score":0.3598000109195709}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6693000197410583},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6444000005722046},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.573199987411499},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.49070000648498535},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.475600004196167},{"id":"https://openalex.org/C204366326","wikidata":"https://www.wikidata.org/wiki/Q3027650","display_name":"Deformation (meteorology)","level":2,"score":0.46149998903274536},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.4115999937057495},{"id":"https://openalex.org/C92757383","wikidata":"https://www.wikidata.org/wiki/Q382497","display_name":"Affine transformation","level":2,"score":0.399399995803833},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.39079999923706055},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.38429999351501465},{"id":"https://openalex.org/C146159030","wikidata":"https://www.wikidata.org/wiki/Q7625099","display_name":"Structure from motion","level":3,"score":0.3598000109195709},{"id":"https://openalex.org/C190470478","wikidata":"https://www.wikidata.org/wiki/Q2370229","display_name":"Invariant (physics)","level":2,"score":0.34769999980926514},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.328900009393692},{"id":"https://openalex.org/C10161872","wikidata":"https://www.wikidata.org/wiki/Q557891","display_name":"Motion estimation","level":2,"score":0.32739999890327454},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.31529998779296875},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.30300000309944153},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.28600001335144043},{"id":"https://openalex.org/C95020103","wikidata":"https://www.wikidata.org/wiki/Q1813492","display_name":"Match moving","level":3,"score":0.2851000130176544},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.2791999876499176},{"id":"https://openalex.org/C3261483","wikidata":"https://www.wikidata.org/wiki/Q119565","display_name":"Frame rate","level":2,"score":0.27129998803138733},{"id":"https://openalex.org/C150627866","wikidata":"https://www.wikidata.org/wiki/Q1076893","display_name":"Field of view","level":2,"score":0.2702000141143799},{"id":"https://openalex.org/C124774092","wikidata":"https://www.wikidata.org/wiki/Q6917782","display_name":"Motion field","level":3,"score":0.2583000063896179}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2602.14376","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.14376","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2602.14376","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.14376","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11","score":0.4693564474582672}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Visual":[0],"Deformation":[1],"Measurement":[2],"(VDM)":[3],"aims":[4],"to":[5,25,35,126],"recover":[6],"dense":[7,63,70,138],"deformation":[8,90,163],"fields":[9],"by":[10,175],"tracking":[11],"surface":[12],"motion":[13,24,64,100],"from":[14,103],"camera":[15],"observations.":[16],"Traditional":[17],"image-based":[18],"methods":[19],"rely":[20],"on":[21],"minimal":[22],"inter-frame":[23],"constrain":[26],"the":[27,44,74,89,142,172,188],"correspondence":[28],"search":[29],"space,":[30],"which":[31],"limits":[32],"their":[33,128],"applicability":[34],"highly":[36],"dynamic":[37],"scenes":[38],"or":[39],"necessitates":[40],"high-speed":[41,195],"cameras":[42],"at":[43],"cost":[45],"of":[46,187,194],"prohibitive":[47],"storage":[48,190],"and":[49,66,105,113,153,191],"computational":[50],"overhead.":[51],"We":[52],"propose":[53,80],"an":[54,81],"event-frame":[55],"fusion":[56],"framework":[57],"that":[58,168],"exploits":[59],"events":[60],"for":[61,68],"temporally":[62,149],"cues":[65],"frames":[67,154],"spatially":[69],"precise":[71],"estimation.":[72],"Revisiting":[73],"solid":[75],"elastic":[76],"modeling":[77],"prior,":[78],"we":[79],"Affine":[82],"Invariant":[83],"Simplicial":[84],"(AIS)":[85],"framework.":[86],"It":[87],"partitions":[88],"field":[91],"into":[92],"linearized":[93],"sub-regions":[94,125],"with":[95,148],"low-parametric":[96],"representation,":[97],"effectively":[98,131],"mitigating":[99],"ambiguities":[101],"arising":[102],"sparse":[104],"noisy":[106],"events.":[107],"To":[108,140],"speed":[109],"up":[110],"parameter":[111],"searching":[112],"reduce":[114],"error":[115,134],"accumulation,":[116],"a":[117,145],"neighborhood-greedy":[118],"optimization":[119],"strategy":[120],"is":[121,155],"introduced,":[122],"enabling":[123],"well-converged":[124],"guide":[127],"poorly-converged":[129],"neighbors,":[130],"suppress":[132],"local":[133],"accumulation":[135],"in":[136,177],"long-term":[137],"tracking.":[139],"evaluate":[141],"proposed":[143],"method,":[144],"benchmark":[146],"dataset":[147],"aligned":[150],"event":[151],"streams":[152],"established,":[156],"encompassing":[157],"over":[158],"120":[159],"sequences":[160],"spanning":[161],"diverse":[162],"scenarios.":[164],"Experimental":[165],"results":[166],"show":[167],"our":[169],"method":[170],"outperforms":[171],"state-of-the-art":[173],"baseline":[174],"1.6%":[176],"survival":[178],"rate.":[179],"Remarkably,":[180],"it":[181],"achieves":[182],"this":[183],"using":[184],"only":[185],"18.9%":[186],"data":[189],"processing":[192],"resources":[193],"video":[196],"methods.":[197]},"counts_by_year":[],"updated_date":"2026-02-18T06:25:47.457606","created_date":"2026-02-18T00:00:00"}