{"id":"https://openalex.org/W1622741890","doi":"https://doi.org/10.1109/lsp.2015.2480097","title":"Structural SVM with Partial Ranking for Activity Segmentation and Classification","display_name":"Structural SVM with Partial Ranking for Activity Segmentation and Classification","publication_year":2015,"publication_date":"2015-09-18","ids":{"openalex":"https://openalex.org/W1622741890","doi":"https://doi.org/10.1109/lsp.2015.2480097","mag":"1622741890"},"language":"en","primary_location":{"id":"doi:10.1109/lsp.2015.2480097","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2015.2480097","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Signal Processing Letters","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://opus.lib.uts.edu.au/bitstream/10453/40982/3/SPL_Guopeng_second_revision.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101460340","display_name":"Guopeng Zhang","orcid":"https://orcid.org/0000-0001-7479-960X"},"institutions":[{"id":"https://openalex.org/I114017466","display_name":"University of Technology Sydney","ror":"https://ror.org/03f0f6041","country_code":"AU","type":"education","lineage":["https://openalex.org/I114017466"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Guopeng Zhang","raw_affiliation_strings":["University of Technology Sydney (UTS), Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Technology Sydney (UTS), Australia","institution_ids":["https://openalex.org/I114017466"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5080014791","display_name":"Massimo Piccardi","orcid":"https://orcid.org/0000-0001-9250-6604"},"institutions":[{"id":"https://openalex.org/I114017466","display_name":"University of Technology Sydney","ror":"https://ror.org/03f0f6041","country_code":"AU","type":"education","lineage":["https://openalex.org/I114017466"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Massimo Piccardi","raw_affiliation_strings":["University of Technology Sydney (UTS), Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Technology Sydney (UTS), Australia","institution_ids":["https://openalex.org/I114017466"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I114017466"],"apc_list":null,"apc_paid":null,"fwci":1.102,"has_fulltext":true,"cited_by_count":12,"citation_normalized_percentile":{"value":0.83950762,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"22","issue":"12","first_page":"2344","last_page":"2348"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9998999834060669,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9998999834060669,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9993000030517578,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.8663796186447144},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7685145139694214},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.733089804649353},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.6823395490646362},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6655442714691162},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6338008046150208},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.6142730712890625},{"id":"https://openalex.org/keywords/ranking-svm","display_name":"Ranking SVM","score":0.6021685004234314},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.5111415982246399},{"id":"https://openalex.org/keywords/constraint","display_name":"Constraint (computer-aided design)","score":0.43609899282455444},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.40447115898132324},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.22965210676193237}],"concepts":[{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.8663796186447144},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7685145139694214},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.733089804649353},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.6823395490646362},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6655442714691162},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6338008046150208},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.6142730712890625},{"id":"https://openalex.org/C124975894","wikidata":"https://www.wikidata.org/wiki/Q7293290","display_name":"Ranking SVM","level":3,"score":0.6021685004234314},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.5111415982246399},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.43609899282455444},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.40447115898132324},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.22965210676193237},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/lsp.2015.2480097","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2015.2480097","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Signal Processing Letters","raw_type":"journal-article"},{"id":"pmh:oai:opus.lib.uts.edu.au:10453/40982","is_oa":true,"landing_page_url":"http://hdl.handle.net/10453/40982","pdf_url":"https://opus.lib.uts.edu.au/bitstream/10453/40982/3/SPL_Guopeng_second_revision.pdf","source":{"id":"https://openalex.org/S4306401357","display_name":"UTS ePRESS (University of Technology Sydney)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I114017466","host_organization_name":"University of Technology Sydney","host_organization_lineage":["https://openalex.org/I114017466"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Journal Article"}],"best_oa_location":{"id":"pmh:oai:opus.lib.uts.edu.au:10453/40982","is_oa":true,"landing_page_url":"http://hdl.handle.net/10453/40982","pdf_url":"https://opus.lib.uts.edu.au/bitstream/10453/40982/3/SPL_Guopeng_second_revision.pdf","source":{"id":"https://openalex.org/S4306401357","display_name":"UTS ePRESS (University of Technology Sydney)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I114017466","host_organization_name":"University of Technology Sydney","host_organization_lineage":["https://openalex.org/I114017466"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Journal Article"},"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.6200000047683716}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W1622741890.pdf","grobid_xml":"https://content.openalex.org/works/W1622741890.grobid-xml"},"referenced_works_count":23,"referenced_works":["https://openalex.org/W182831726","https://openalex.org/W326763573","https://openalex.org/W1515020792","https://openalex.org/W1973441361","https://openalex.org/W1978511849","https://openalex.org/W1983500014","https://openalex.org/W2007964250","https://openalex.org/W2012592962","https://openalex.org/W2019586054","https://openalex.org/W2078046413","https://openalex.org/W2105644991","https://openalex.org/W2105842272","https://openalex.org/W2136057366","https://openalex.org/W2136064009","https://openalex.org/W2145835757","https://openalex.org/W2147898188","https://openalex.org/W2153635508","https://openalex.org/W2546945975","https://openalex.org/W4206733017","https://openalex.org/W4285719527","https://openalex.org/W6675760969","https://openalex.org/W6675783020","https://openalex.org/W6681579763"],"related_works":["https://openalex.org/W2345184372","https://openalex.org/W1035545585","https://openalex.org/W2136184105","https://openalex.org/W2187500075","https://openalex.org/W2041399278","https://openalex.org/W1592878262","https://openalex.org/W2160451891","https://openalex.org/W2937631562","https://openalex.org/W2736898786","https://openalex.org/W2913952424"],"abstract_inverted_index":{"Structural":[0],"SVM":[1,29,70,85,130],"is":[2,53],"an":[3],"extension":[4],"of":[5,14,27,35,44,68,146,154],"the":[6,11,25,32,56,64,105,111,127,144,147],"support":[7],"vector":[8],"machine":[9],"for":[10],"joint":[12],"prediction":[13],"structured":[15],"labels":[16],"from":[17],"multiple":[18],"measurements.":[19],"Following":[20],"a":[21,39,82,132],"large":[22],"margin":[23],"principle,":[24],"training":[26],"structural":[28,69,84,129],"ensures":[30],"that":[31,43,110],"ground-truth":[33],"labeling":[34],"each":[36],"sample":[37],"receives":[38],"score":[40,51],"higher":[41,122,141],"than":[42,125,143],"any":[45],"other":[46,57],"labeling.":[47],"However,":[48],"no":[49],"specific":[50],"ranking":[52],"imposed":[54],"among":[55],"labelings.":[58],"In":[59],"this":[60],"letter,":[61],"we":[62],"extend":[63],"standard":[65],"constraint":[66],"set":[67],"with":[71,95],"constraints":[72],"between":[73],"\u201calmost-correct\u201d":[74],"labelings":[75],"and":[76,93,104,117,121,131,156],"less":[77],"desirable":[78],"ones":[79],"to":[80],"obtain":[81],"partial-ranking":[83],"(PR-SSVM)":[86],"approach.":[87],"Experimental":[88],"results":[89],"on":[90,149],"action":[91],"segmentation":[92],"classification":[94],"two":[96],"challenging":[97],"datasets":[98,151],"(the":[99],"TUM":[100],"Kitchen":[101],"mocap":[102],"dataset":[103],"CMU-MMAC":[106],"video":[107],"dataset)":[108],"show":[109],"proposed":[112,137],"method":[113,138],"achieves":[114,140],"better":[115],"detection":[116],"false":[118],"alarm":[119],"rates":[120],"F1":[123],"scores":[124],"both":[126],"conventional":[128],"comparable":[133],"unstructured":[134],"predictor.":[135],"The":[136],"also":[139],"accuracy":[142],"state":[145],"art":[148],"these":[150],"in":[152],"excess":[153],"14":[155],"31":[157],"percentage":[158],"points,":[159],"respectively.":[160]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":3},{"year":2015,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}