{"id":"https://openalex.org/W2791873344","doi":"https://doi.org/10.1109/icip.2017.8296360","title":"Online multi-object tracking with convolutional neural networks","display_name":"Online multi-object tracking with convolutional neural networks","publication_year":2017,"publication_date":"2017-09-01","ids":{"openalex":"https://openalex.org/W2791873344","doi":"https://doi.org/10.1109/icip.2017.8296360","mag":"2791873344"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2017.8296360","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2017.8296360","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Image Processing (ICIP)","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/A5100630554","display_name":"Long Chen","orcid":"https://orcid.org/0000-0002-2079-3867"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Long Chen","raw_affiliation_strings":["Department of Computer Science and Technology, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074577884","display_name":"Haizhou Ai","orcid":"https://orcid.org/0000-0002-0166-5755"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haizhou Ai","raw_affiliation_strings":["Department of Computer Science and Technology, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090459802","display_name":"Chong Shang","orcid":"https://orcid.org/0000-0003-4822-1489"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chong Shang","raw_affiliation_strings":["Department of Computer Science and Technology, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069706571","display_name":"Zijie Zhuang","orcid":"https://orcid.org/0000-0003-2132-4197"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zijie Zhuang","raw_affiliation_strings":["Department of Computer Science and Technology, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5001405009","display_name":"Bo Bai","orcid":"https://orcid.org/0000-0003-4796-8249"},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bo Bai","raw_affiliation_strings":["Huawei Technologies, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Huawei Technologies, Beijing, China","institution_ids":["https://openalex.org/I2250955327"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100630554"],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":4.8242,"has_fulltext":false,"cited_by_count":118,"citation_normalized_percentile":{"value":0.97112835,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"645","last_page":"649"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9998000264167786,"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":0.9998000264167786,"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/T12486","display_name":"Food Supply Chain Traceability","score":0.9882000088691711,"subfield":{"id":"https://openalex.org/subfields/1106","display_name":"Food Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11667","display_name":"Advanced Chemical Sensor Technologies","score":0.9872999787330627,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical 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/computer-science","display_name":"Computer science","score":0.807879626750946},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.8062446117401123},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.7066417932510376},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6554234623908997},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6299373507499695},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6031726598739624},{"id":"https://openalex.org/keywords/online-learning","display_name":"Online learning","score":0.5922069549560547},{"id":"https://openalex.org/keywords/video-tracking","display_name":"Video tracking","score":0.5662134289741516},{"id":"https://openalex.org/keywords/intuition","display_name":"Intuition","score":0.5077415704727173},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5048993229866028},{"id":"https://openalex.org/keywords/active-appearance-model","display_name":"Active appearance model","score":0.4954029321670532},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4310497045516968},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.3794446289539337},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3293789029121399},{"id":"https://openalex.org/keywords/multimedia","display_name":"Multimedia","score":0.09794437885284424},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.08349362015724182}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.807879626750946},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.8062446117401123},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.7066417932510376},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6554234623908997},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6299373507499695},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6031726598739624},{"id":"https://openalex.org/C2986087404","wikidata":"https://www.wikidata.org/wiki/Q15946010","display_name":"Online learning","level":2,"score":0.5922069549560547},{"id":"https://openalex.org/C202474056","wikidata":"https://www.wikidata.org/wiki/Q1931635","display_name":"Video tracking","level":3,"score":0.5662134289741516},{"id":"https://openalex.org/C132010649","wikidata":"https://www.wikidata.org/wiki/Q189222","display_name":"Intuition","level":2,"score":0.5077415704727173},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5048993229866028},{"id":"https://openalex.org/C83248878","wikidata":"https://www.wikidata.org/wiki/Q344000","display_name":"Active appearance model","level":3,"score":0.4954029321670532},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4310497045516968},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.3794446289539337},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3293789029121399},{"id":"https://openalex.org/C49774154","wikidata":"https://www.wikidata.org/wiki/Q131765","display_name":"Multimedia","level":1,"score":0.09794437885284424},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.08349362015724182},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip.2017.8296360","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2017.8296360","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W1497265063","https://openalex.org/W1521019969","https://openalex.org/W1536680647","https://openalex.org/W1686810756","https://openalex.org/W1857884451","https://openalex.org/W2053744956","https://openalex.org/W2055022211","https://openalex.org/W2122088301","https://openalex.org/W2124781496","https://openalex.org/W2148958980","https://openalex.org/W2160337655","https://openalex.org/W2163605009","https://openalex.org/W2186094539","https://openalex.org/W2211629196","https://openalex.org/W2214352687","https://openalex.org/W2225887246","https://openalex.org/W2252355370","https://openalex.org/W2252862078","https://openalex.org/W2468912036","https://openalex.org/W2474389331","https://openalex.org/W2547098537","https://openalex.org/W2555375762","https://openalex.org/W2613718673","https://openalex.org/W2953106684","https://openalex.org/W2962835968","https://openalex.org/W2964253307","https://openalex.org/W3104218139","https://openalex.org/W4295331127","https://openalex.org/W6620707391","https://openalex.org/W6637373629","https://openalex.org/W6638969170","https://openalex.org/W6677999991","https://openalex.org/W6684191040","https://openalex.org/W6703518758"],"related_works":["https://openalex.org/W17155033","https://openalex.org/W3207760230","https://openalex.org/W1496222301","https://openalex.org/W1590307681","https://openalex.org/W2012200063","https://openalex.org/W2132541102","https://openalex.org/W2963010494","https://openalex.org/W2107332757","https://openalex.org/W3201620372","https://openalex.org/W2132182117"],"abstract_inverted_index":{"In":[0,19],"this":[1],"paper,":[2],"we":[3,21,61],"propose":[4],"a":[5,28,33,86],"novel":[6],"online":[7,59],"multi-object":[8],"tracking":[9,83],"(MOT)":[10],"framework,":[11],"which":[12],"exploits":[13],"features":[14],"from":[15,39],"multiple":[16],"convolutional":[17],"layers.":[18],"particular,":[20],"use":[22,32],"the":[23,43,54,72,81,92,95],"top":[24],"layer":[25,35],"to":[26,36,90],"formulate":[27],"category-level":[29],"classifier":[30],"and":[31,94],"lower":[34,46],"identify":[37],"instances":[38],"one":[40],"category":[41],"under":[42],"intuition":[44],"that":[45],"layers":[47],"contain":[48],"much":[49],"more":[50],"details.":[51],"To":[52],"avoid":[53],"computational":[55],"cost":[56],"caused":[57],"by":[58],"fine-tuning,":[60],"train":[62],"our":[63,99],"appearance":[64,74],"model":[65],"with":[66],"an":[67],"offline":[68],"learning":[69],"strategy":[70],"using":[71],"historical":[73],"reserved":[75],"for":[76],"each":[77],"object.":[78],"We":[79],"evaluate":[80],"proposed":[82],"framework":[84],"on":[85],"popular":[87],"MOT":[88],"benchmark":[89],"demonstrate":[91],"effectiveness":[93],"state-of-the-art":[96],"performance":[97],"of":[98],"tracker.":[100]},"counts_by_year":[{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":19},{"year":2021,"cited_by_count":21},{"year":2020,"cited_by_count":19},{"year":2019,"cited_by_count":26},{"year":2018,"cited_by_count":8}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}