{"id":"https://openalex.org/W4414170638","doi":"https://doi.org/10.1109/avss65446.2025.11149974","title":"A Depth-Aware Robust Multi-Object Tracker for Crowded Scene by Re-Prioritizing Association Order","display_name":"A Depth-Aware Robust Multi-Object Tracker for Crowded Scene by Re-Prioritizing Association Order","publication_year":2025,"publication_date":"2025-08-11","ids":{"openalex":"https://openalex.org/W4414170638","doi":"https://doi.org/10.1109/avss65446.2025.11149974"},"language":"en","primary_location":{"id":"doi:10.1109/avss65446.2025.11149974","is_oa":false,"landing_page_url":"https://doi.org/10.1109/avss65446.2025.11149974","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Advanced Visual and Signal-Based Systems (AVSS)","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/A5047672937","display_name":"Cheng-Yen Yang","orcid":"https://orcid.org/0009-0004-2631-6756"},"institutions":[{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Cheng-Yen Yang","raw_affiliation_strings":["University of Washington,Information Processing Lab,USA"],"affiliations":[{"raw_affiliation_string":"University of Washington,Information Processing Lab,USA","institution_ids":["https://openalex.org/I201448701"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101699930","display_name":"Hsiang-Wei Huang","orcid":"https://orcid.org/0000-0003-0373-9487"},"institutions":[{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hsiang-Wei Huang","raw_affiliation_strings":["University of Washington,Information Processing Lab,USA"],"affiliations":[{"raw_affiliation_string":"University of Washington,Information Processing Lab,USA","institution_ids":["https://openalex.org/I201448701"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072487344","display_name":"Kuang-Ming Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kuang-Ming Chen","raw_affiliation_strings":["University of Washington,Information Processing Lab,USA"],"affiliations":[{"raw_affiliation_string":"University of Washington,Information Processing Lab,USA","institution_ids":["https://openalex.org/I201448701"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068673495","display_name":"K. Li","orcid":"https://orcid.org/0009-0007-9770-2234"},"institutions":[{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kunjun Li","raw_affiliation_strings":["University of Washington,Information Processing Lab,USA"],"affiliations":[{"raw_affiliation_string":"University of Washington,Information Processing Lab,USA","institution_ids":["https://openalex.org/I201448701"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017289206","display_name":"Farron Wallace","orcid":"https://orcid.org/0000-0002-3690-9588"},"institutions":[{"id":"https://openalex.org/I4210131645","display_name":"NOAA National Marine Fisheries Service Southeast Fisheries Science Center","ror":"https://ror.org/0396y0w87","country_code":"US","type":"government","lineage":["https://openalex.org/I106745318","https://openalex.org/I1308126019","https://openalex.org/I1343035065","https://openalex.org/I4210131645"]},{"id":"https://openalex.org/I1308126019","display_name":"National Oceanic and Atmospheric Administration","ror":"https://ror.org/02z5nhe81","country_code":"US","type":"funder","lineage":["https://openalex.org/I1308126019","https://openalex.org/I1343035065"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Farron Wallace","raw_affiliation_strings":["National Oceanic and Atmospheric Administration (NOAA),Southeast Fisheries Science Center,USA"],"affiliations":[{"raw_affiliation_string":"National Oceanic and Atmospheric Administration (NOAA),Southeast Fisheries Science Center,USA","institution_ids":["https://openalex.org/I1308126019","https://openalex.org/I4210131645"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103565961","display_name":"Chung-I Huang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210107525","display_name":"National Center for High-Performance Computing","ror":"https://ror.org/01jpzd518","country_code":"TW","type":"facility","lineage":["https://openalex.org/I4210107525","https://openalex.org/I4210128167","https://openalex.org/I4210166867"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Chung-I Huang","raw_affiliation_strings":["National Center for High-Performance Computing (NCHC),Taiwan"],"affiliations":[{"raw_affiliation_string":"National Center for High-Performance Computing (NCHC),Taiwan","institution_ids":["https://openalex.org/I4210107525"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101702810","display_name":"Jenq\u2013Neng Hwang","orcid":"https://orcid.org/0000-0002-8877-2421"},"institutions":[{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jenq-Neng Hwang","raw_affiliation_strings":["University of Washington,Information Processing Lab,USA"],"affiliations":[{"raw_affiliation_string":"University of Washington,Information Processing Lab,USA","institution_ids":["https://openalex.org/I201448701"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5047672937"],"corresponding_institution_ids":["https://openalex.org/I201448701"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.23281299,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","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/T10331","display_name":"Video Surveillance and Tracking Methods","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/T10531","display_name":"Advanced Vision and Imaging","score":0.9919000267982483,"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/T12389","display_name":"Infrared Target Detection Methodologies","score":0.9916999936103821,"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/robustness","display_name":"Robustness (evolution)","score":0.8284000158309937},{"id":"https://openalex.org/keywords/data-association","display_name":"Data association","score":0.6205000281333923},{"id":"https://openalex.org/keywords/association","display_name":"Association (psychology)","score":0.5460000038146973},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.48660001158714294},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.430400013923645},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3382999897003174}],"concepts":[{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.8284000158309937},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6837000250816345},{"id":"https://openalex.org/C2983325608","wikidata":"https://www.wikidata.org/wiki/Q17084606","display_name":"Data association","level":3,"score":0.6205000281333923},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6121000051498413},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5834000110626221},{"id":"https://openalex.org/C142853389","wikidata":"https://www.wikidata.org/wiki/Q744778","display_name":"Association (psychology)","level":2,"score":0.5460000038146973},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.48660001158714294},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.430400013923645},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3382999897003174},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32269999384880066},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.31279999017715454},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.296099990606308},{"id":"https://openalex.org/C2983787585","wikidata":"https://www.wikidata.org/wiki/Q93586","display_name":"Feature matching","level":3,"score":0.29499998688697815},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.28929999470710754},{"id":"https://openalex.org/C2987395694","wikidata":"https://www.wikidata.org/wiki/Q557891","display_name":"Feature tracking","level":3,"score":0.28760001063346863},{"id":"https://openalex.org/C193524817","wikidata":"https://www.wikidata.org/wiki/Q386780","display_name":"Association rule learning","level":2,"score":0.26980000734329224},{"id":"https://openalex.org/C2986492983","wikidata":"https://www.wikidata.org/wiki/Q861092","display_name":"Image matching","level":3,"score":0.2644999921321869},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2574999928474426}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/avss65446.2025.11149974","is_oa":false,"landing_page_url":"https://doi.org/10.1109/avss65446.2025.11149974","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Advanced Visual and Signal-Based Systems (AVSS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320338437","display_name":"Southeast Fisheries Science Center","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W2252355370","https://openalex.org/W2291627510","https://openalex.org/W2603203130","https://openalex.org/W3084173793","https://openalex.org/W3086436251","https://openalex.org/W3095753995","https://openalex.org/W3104218139","https://openalex.org/W3104778224","https://openalex.org/W4283748233","https://openalex.org/W4286904999","https://openalex.org/W4312473433","https://openalex.org/W4313072323","https://openalex.org/W4322616103","https://openalex.org/W4386075559","https://openalex.org/W4386076204","https://openalex.org/W4386083103","https://openalex.org/W4393153514","https://openalex.org/W4394842583","https://openalex.org/W4394862566","https://openalex.org/W4400721625","https://openalex.org/W4401307635","https://openalex.org/W4402727359","https://openalex.org/W4404573408","https://openalex.org/W4405974723","https://openalex.org/W4407458081","https://openalex.org/W4408354060"],"related_works":[],"abstract_inverted_index":{"Occlusion":[0],"remains":[1],"a":[2,34,54],"major":[3],"challenge":[4],"in":[5,61,110],"online":[6],"Multi-Object":[7],"Tracking":[8],"(MOT),":[9],"where":[10],"existing":[11,91],"multi-stage":[12],"association":[13,44,52,95],"methods":[14],"often":[15],"rely":[16],"on":[17,101],"detection":[18],"confidence":[19],"scores":[20],"despite":[21],"their":[22],"weak":[23],"correlation":[24],"with":[25,53],"occlusion,":[26],"leading":[27],"to":[28,82],"frequent":[29],"errors.":[30],"We":[31],"propose":[32],"DARUMA,":[33],"depth-aware":[35,75],"MOT":[36,92],"framework":[37],"that":[38,104],"prioritizes":[39],"non-occluded":[40],"objects":[41],"using":[42],"occlusion-aware":[43],"by":[45],"re-prioritizing":[46],"the":[47],"matching":[48],"order":[49],"and":[50,63,78],"refines":[51],"depth-weighted":[55],"cost":[56],"metric":[57],"for":[58],"improved":[59],"robustness":[60,96],"occluded":[62],"depth-varying":[64],"environments.":[65],"Additionally,":[66],"we":[67],"introduce":[68],"Generic":[69],"Observation-Centric":[70],"Momentum":[71],"(GOCM),":[72],"which":[73],"integrates":[74,89],"velocity":[76],"estimation":[77],"confidence-weighted":[79],"historical":[80],"observations":[81],"enhance":[83],"motion":[84],"modeling.":[85],"Our":[86],"method":[87],"can":[88],"into":[90],"frameworks,":[93],"improving":[94],"without":[97],"additional":[98],"supervision.Extensive":[99],"evaluations":[100],"DanceTrack":[102],"demonstrate":[103],"DARUMA":[105],"achieves":[106],"state-of-the-art":[107],"performance,":[108],"particularly":[109],"complex,":[111],"occlusion-heavy":[112],"scenarios.":[113]},"counts_by_year":[],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-10T00:00:00"}