{"id":"https://openalex.org/W2779095146","doi":"https://doi.org/10.1109/dicta.2017.8227424","title":"Deformable and Occluded Object Tracking via Graph Learning","display_name":"Deformable and Occluded Object Tracking via Graph Learning","publication_year":2017,"publication_date":"2017-11-01","ids":{"openalex":"https://openalex.org/W2779095146","doi":"https://doi.org/10.1109/dicta.2017.8227424","mag":"2779095146"},"language":"en","primary_location":{"id":"doi:10.1109/dicta.2017.8227424","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dicta.2017.8227424","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 International Conference on Digital Image Computing: Techniques and Applications (DICTA)","raw_type":"proceedings-article"},"type":"article","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/A5101655190","display_name":"Wei Han","orcid":"https://orcid.org/0000-0003-0154-5574"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":true,"raw_author_name":"Wei Han","raw_affiliation_strings":["School of Electrical and Electronic Engineering, Nanyang Technological University"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Electronic Engineering, Nanyang Technological University","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061746912","display_name":"Guang-Bin Huang","orcid":"https://orcid.org/0000-0002-2480-4965"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Guang-Bin Huang","raw_affiliation_strings":["School of Electrical and Electronic Engineering, Nanyang Technological University"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Electronic Engineering, Nanyang Technological University","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5057937760","display_name":"Dongshun Cui","orcid":"https://orcid.org/0000-0002-9703-0120"},"institutions":[{"id":"https://openalex.org/I4210094970","display_name":"Energy Research Institute","ror":"https://ror.org/00ndnb620","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210094970","https://openalex.org/I4210142748"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dongshun Cui","raw_affiliation_strings":["Energy Research Institute NTU (ERI@N), Interdisciplinary Graduate School"],"affiliations":[{"raw_affiliation_string":"Energy Research Institute NTU (ERI@N), Interdisciplinary Graduate School","institution_ids":["https://openalex.org/I4210094970"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5101655190"],"corresponding_institution_ids":["https://openalex.org/I172675005"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.19235235,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"7574","issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":1.0,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":1.0,"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":0.9918000102043152,"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/T11398","display_name":"Hand Gesture Recognition Systems","score":0.964900016784668,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.6946895122528076},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6861959099769592},{"id":"https://openalex.org/keywords/minimum-bounding-box","display_name":"Minimum bounding box","score":0.6262727975845337},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6257613301277161},{"id":"https://openalex.org/keywords/video-tracking","display_name":"Video tracking","score":0.6199737787246704},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.6198093295097351},{"id":"https://openalex.org/keywords/bounding-overwatch","display_name":"Bounding overwatch","score":0.610789954662323},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.4798157215118408},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.4427529573440552},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.4355008006095886},{"id":"https://openalex.org/keywords/active-appearance-model","display_name":"Active appearance model","score":0.4205668270587921},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.38355088233947754},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.37944352626800537},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.2503036558628082},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.15946635603904724}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6946895122528076},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6861959099769592},{"id":"https://openalex.org/C147037132","wikidata":"https://www.wikidata.org/wiki/Q6865426","display_name":"Minimum bounding box","level":3,"score":0.6262727975845337},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6257613301277161},{"id":"https://openalex.org/C202474056","wikidata":"https://www.wikidata.org/wiki/Q1931635","display_name":"Video tracking","level":3,"score":0.6199737787246704},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.6198093295097351},{"id":"https://openalex.org/C63584917","wikidata":"https://www.wikidata.org/wiki/Q333286","display_name":"Bounding overwatch","level":2,"score":0.610789954662323},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.4798157215118408},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.4427529573440552},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.4355008006095886},{"id":"https://openalex.org/C83248878","wikidata":"https://www.wikidata.org/wiki/Q344000","display_name":"Active appearance model","level":3,"score":0.4205668270587921},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.38355088233947754},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.37944352626800537},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2503036558628082},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.15946635603904724},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C19417346","wikidata":"https://www.wikidata.org/wiki/Q7922","display_name":"Pedagogy","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/dicta.2017.8227424","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dicta.2017.8227424","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 International Conference on Digital Image Computing: Techniques and Applications (DICTA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.46000000834465027}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W1513768190","https://openalex.org/W1807914171","https://openalex.org/W1895982061","https://openalex.org/W1960880753","https://openalex.org/W1967973024","https://openalex.org/W1979089718","https://openalex.org/W1997121481","https://openalex.org/W2003060733","https://openalex.org/W2024029849","https://openalex.org/W2024657922","https://openalex.org/W2026783802","https://openalex.org/W2034938692","https://openalex.org/W2044986361","https://openalex.org/W2047237558","https://openalex.org/W2066513304","https://openalex.org/W2089961441","https://openalex.org/W2098854771","https://openalex.org/W2098941887","https://openalex.org/W2103846358","https://openalex.org/W2118246710","https://openalex.org/W2124211486","https://openalex.org/W2129058790","https://openalex.org/W2132103241","https://openalex.org/W2140595412","https://openalex.org/W2150000644","https://openalex.org/W2154889144","https://openalex.org/W2156757627","https://openalex.org/W2158827467","https://openalex.org/W2162383208","https://openalex.org/W2163532725","https://openalex.org/W2165037244","https://openalex.org/W2167089254","https://openalex.org/W2168802423","https://openalex.org/W2293873019","https://openalex.org/W2395596584","https://openalex.org/W2429528072","https://openalex.org/W2545274162","https://openalex.org/W2753461371","https://openalex.org/W6638399501","https://openalex.org/W6662317391","https://openalex.org/W6683832244","https://openalex.org/W6683886257"],"related_works":["https://openalex.org/W4237171675","https://openalex.org/W3036286480","https://openalex.org/W4287027631","https://openalex.org/W3192357901","https://openalex.org/W2387360586","https://openalex.org/W2952736415","https://openalex.org/W3209723314","https://openalex.org/W3205398323","https://openalex.org/W2883297582","https://openalex.org/W4390524233"],"abstract_inverted_index":{"Object":[0],"deformation":[1,19,31],"and":[2,20,32,84,101],"occlusion":[3],"are":[4,63],"ubiquitous":[5],"problems":[6],"for":[7],"visual":[8],"tracking.":[9],"Though":[10],"many":[11],"efforts":[12],"have":[13],"been":[14],"made":[15],"to":[16,45,91],"handle":[17,46],"object":[18,104],"occlusion,":[21],"most":[22],"existing":[23],"tracking":[24,43],"algorithms":[25],"fail":[26],"in":[27,59],"case":[28],"of":[29,67],"large":[30],"severe":[33],"occlusion.":[34],"In":[35],"this":[36],"paper,":[37],"we":[38,54],"propose":[39],"a":[40,56],"graph":[41,74,100],"learning-based":[42],"framework":[44,110],"both":[47,68],"challenges.":[48],"For":[49],"each":[50],"consecutive":[51],"frame":[52,94],"pair,":[53],"construct":[55],"weighted":[57],"graph,":[58],"which":[60],"the":[61,64,73,82,92,98,103,112,119,124,128],"nodes":[62,95],"local":[65],"parts":[66],"frames.":[69],"Our":[70],"algorithm":[71],"optimizes":[72],"similarity":[75],"matrix":[76],"until":[77],"two":[78],"disconnected":[79],"subgraphs":[80],"separate":[81],"foreground":[83,114],"background":[85],"nodes.":[86],"We":[87],"assign":[88],"foreground/background":[89],"labels":[90],"current":[93],"based":[96],"on":[97,118],"learned":[99],"estimate":[102],"bounding":[105],"box":[106],"under":[107],"an":[108],"optimization":[109],"with":[111],"predicted":[113],"parts.":[115],"Experimental":[116],"results":[117],"Deform-SOT":[120],"dataset":[121],"shows":[122],"that":[123],"proposed":[125],"method":[126],"achieves":[127],"state-of-the-art":[129],"performance.":[130]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
