{"id":"https://openalex.org/W7155942716","doi":"https://doi.org/10.48550/arxiv.2604.22476","title":"All Eyes on the Workflow: Automated and Efficient Event Discovery from Video Streams","display_name":"All Eyes on the Workflow: Automated and Efficient Event Discovery from Video Streams","publication_year":2026,"publication_date":"2026-04-24","ids":{"openalex":"https://openalex.org/W7155942716","doi":"https://doi.org/10.48550/arxiv.2604.22476"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.22476","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.22476","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.2604.22476","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5134733448","display_name":"Marco Pegoraro","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pegoraro, Marco","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073921488","display_name":"Jonas Seng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Seng, Jonas","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134687383","display_name":"Dustin Heller","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Heller, Dustin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134697158","display_name":"Wil M. P. van der Aalst","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"van der Aalst, Wil M. P.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5037636074","display_name":"Kristian Kersting","orcid":"https://orcid.org/0000-0002-2873-9152"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kersting, Kristian","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/T10703","display_name":"Business Process Modeling and Analysis","score":0.9664000272750854,"subfield":{"id":"https://openalex.org/subfields/1404","display_name":"Management Information Systems"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T10703","display_name":"Business Process Modeling and Analysis","score":0.9664000272750854,"subfield":{"id":"https://openalex.org/subfields/1404","display_name":"Management Information Systems"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12127","display_name":"Software System Performance and Reliability","score":0.002300000051036477,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T10679","display_name":"Service-Oriented Architecture and Web Services","score":0.0015999999595806003,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.7124999761581421},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.6707000136375427},{"id":"https://openalex.org/keywords/process-mining","display_name":"Process mining","score":0.5737000107765198},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5292999744415283},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.475600004196167},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.4262999892234802},{"id":"https://openalex.org/keywords/data-stream-mining","display_name":"Data stream mining","score":0.40959998965263367},{"id":"https://openalex.org/keywords/basis","display_name":"Basis (linear algebra)","score":0.39989998936653137},{"id":"https://openalex.org/keywords/obstacle","display_name":"Obstacle","score":0.38960000872612}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7681999802589417},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.7124999761581421},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.6707000136375427},{"id":"https://openalex.org/C124670913","wikidata":"https://www.wikidata.org/wiki/Q2608526","display_name":"Process mining","level":5,"score":0.5737000107765198},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5651000142097473},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5322999954223633},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5292999744415283},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.475600004196167},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.4262999892234802},{"id":"https://openalex.org/C89198739","wikidata":"https://www.wikidata.org/wiki/Q3079880","display_name":"Data stream mining","level":2,"score":0.40959998965263367},{"id":"https://openalex.org/C12426560","wikidata":"https://www.wikidata.org/wiki/Q189569","display_name":"Basis (linear algebra)","level":2,"score":0.39989998936653137},{"id":"https://openalex.org/C2776650193","wikidata":"https://www.wikidata.org/wiki/Q264661","display_name":"Obstacle","level":2,"score":0.38960000872612},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.37560001015663147},{"id":"https://openalex.org/C93453677","wikidata":"https://www.wikidata.org/wiki/Q1017580","display_name":"Business process discovery","level":5,"score":0.37119999527931213},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3521000146865845},{"id":"https://openalex.org/C85345410","wikidata":"https://www.wikidata.org/wiki/Q851587","display_name":"Business process","level":3,"score":0.35199999809265137},{"id":"https://openalex.org/C76956256","wikidata":"https://www.wikidata.org/wiki/Q27610560","display_name":"Process modeling","level":3,"score":0.32829999923706055},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.326200008392334},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.3098999857902527},{"id":"https://openalex.org/C2987896495","wikidata":"https://www.wikidata.org/wiki/Q5416716","display_name":"Event data","level":3,"score":0.30410000681877136},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.30399999022483826},{"id":"https://openalex.org/C120567893","wikidata":"https://www.wikidata.org/wiki/Q1582085","display_name":"Knowledge extraction","level":2,"score":0.29600000381469727},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.28519999980926514},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.26840001344680786},{"id":"https://openalex.org/C65483669","wikidata":"https://www.wikidata.org/wiki/Q3536669","display_name":"Video processing","level":2,"score":0.2639999985694885},{"id":"https://openalex.org/C80309976","wikidata":"https://www.wikidata.org/wiki/Q7007379","display_name":"Business process management","level":4,"score":0.2531999945640564}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.22476","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.22476","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.2604.22476","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.22476","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":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Disciplines":[0],"such":[1],"as":[2,42,53,121],"business":[3],"process":[4,7,27,124,146],"management":[5],"and":[6,90],"mining":[8,125],"aid":[9],"organizations":[10],"by":[11,81],"discovering":[12],"insights":[13],"about":[14],"processes":[15],"on":[16,47,62],"the":[17,109,132,145,148],"basis":[18],"of":[19,50,116],"recorded":[20],"event":[21,77],"data.":[22,134],"However,":[23],"an":[24,73],"obstacle":[25],"to":[26,75,84,105,108,130],"analysis":[28],"is":[29,102],"data":[30,34,78],"multi-modality:":[31],"for":[32],"instance,":[33],"in":[35,147],"video":[36,110],"form":[37],"are":[38,119],"not":[39],"directly":[40],"interpretable":[41,120],"events.":[43,122],"Existing":[44],"approaches":[45],"rely":[46,61],"a":[48],"dictionary":[49],"activity":[51],"label":[52],"input,":[54],"cannot":[55],"provide":[56],"frame-by-frame":[57],"labeling":[58],"explanations,":[59],"or":[60],"superseded":[63],"computer":[64],"vision":[65],"techniques.":[66],"In":[67],"this":[68],"work,":[69],"we":[70],"present":[71],"SnapLog,":[72],"approach":[74,139],"extract":[76],"from":[79],"videos":[80],"converting":[82],"frames":[83,117],"feature":[85],"vectors":[86],"using":[87],"image":[88],"embeddings":[89],"performing":[91],"temporal":[92],"segmentation":[93],"through":[94],"frame-wise":[95],"similarity":[96],"matrices.":[97],"A":[98],"generalized":[99],"few-shot":[100],"classification":[101],"then":[103],"used":[104,129],"assign":[106],"labels":[107],"segments,":[111],"yielding":[112],"labeled,":[113],"timestamped":[114],"sub-sequences":[115],"that":[118,137,142],"Conventional":[123],"techniques":[126],"can":[127],"be":[128],"analyze":[131],"resulting":[133],"We":[135],"show":[136],"our":[138],"produces":[140],"logs":[141],"accurately":[143],"reflect":[144],"videos.":[149]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-04-28T00:00:00"}
