{"id":"https://openalex.org/W2576085163","doi":"https://doi.org/10.1109/icpr.2016.7899807","title":"Deep motion features for visual tracking","display_name":"Deep motion features for visual tracking","publication_year":2016,"publication_date":"2016-12-01","ids":{"openalex":"https://openalex.org/W2576085163","doi":"https://doi.org/10.1109/icpr.2016.7899807","mag":"2576085163"},"language":"en","primary_location":{"id":"doi:10.1109/icpr.2016.7899807","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2016.7899807","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 23rd International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-137896","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5020279135","display_name":"Susanna Gladh","orcid":null},"institutions":[{"id":"https://openalex.org/I102134673","display_name":"Link\u00f6ping University","ror":"https://ror.org/05ynxx418","country_code":"SE","type":"education","lineage":["https://openalex.org/I102134673"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Susanna Gladh","raw_affiliation_strings":["Department of Electrical Engineering, Link\u00f6ping University, Sweden"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Link\u00f6ping University, Sweden","institution_ids":["https://openalex.org/I102134673"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068158266","display_name":"Martin Danelljan","orcid":"https://orcid.org/0000-0001-6144-9520"},"institutions":[{"id":"https://openalex.org/I102134673","display_name":"Link\u00f6ping University","ror":"https://ror.org/05ynxx418","country_code":"SE","type":"education","lineage":["https://openalex.org/I102134673"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Martin Danelljan","raw_affiliation_strings":["Department of Electrical Engineering, Link\u00f6ping University, Sweden"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Link\u00f6ping University, Sweden","institution_ids":["https://openalex.org/I102134673"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100760570","display_name":"Fahad Shahbaz Khan","orcid":"https://orcid.org/0000-0002-4263-3143"},"institutions":[{"id":"https://openalex.org/I102134673","display_name":"Link\u00f6ping University","ror":"https://ror.org/05ynxx418","country_code":"SE","type":"education","lineage":["https://openalex.org/I102134673"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Fahad Shahbaz Khan","raw_affiliation_strings":["Department of Electrical Engineering, Link\u00f6ping University, Sweden"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Link\u00f6ping University, Sweden","institution_ids":["https://openalex.org/I102134673"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5042087981","display_name":"Michael Felsberg","orcid":"https://orcid.org/0000-0002-6096-3648"},"institutions":[{"id":"https://openalex.org/I102134673","display_name":"Link\u00f6ping University","ror":"https://ror.org/05ynxx418","country_code":"SE","type":"education","lineage":["https://openalex.org/I102134673"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Michael Felsberg","raw_affiliation_strings":["Department of Electrical Engineering, Link\u00f6ping University, Sweden"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Link\u00f6ping University, Sweden","institution_ids":["https://openalex.org/I102134673"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I102134673"],"apc_list":null,"apc_paid":null,"fwci":3.0193,"has_fulltext":false,"cited_by_count":86,"citation_normalized_percentile":{"value":0.96064431,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"1243","last_page":"1248"},"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9994000196456909,"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":0.9991999864578247,"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/computer-vision","display_name":"Computer vision","score":0.7574584484100342},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7234417200088501},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6664851307868958},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.5302830338478088},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.5134697556495667},{"id":"https://openalex.org/keywords/computer-graphics","display_name":"Computer graphics (images)","score":0.38303083181381226}],"concepts":[{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7574584484100342},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7234417200088501},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6664851307868958},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.5302830338478088},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.5134697556495667},{"id":"https://openalex.org/C121684516","wikidata":"https://www.wikidata.org/wiki/Q7600677","display_name":"Computer graphics (images)","level":1,"score":0.38303083181381226},{"id":"https://openalex.org/C19417346","wikidata":"https://www.wikidata.org/wiki/Q7922","display_name":"Pedagogy","level":1,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icpr.2016.7899807","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2016.7899807","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 23rd International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"},{"id":"pmh:oai:DiVA.org:liu-137896","is_oa":true,"landing_page_url":"http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-137896","pdf_url":null,"source":{"id":"https://openalex.org/S4306400838","display_name":"DiVA (Linkoping University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":{"id":"pmh:oai:DiVA.org:liu-137896","is_oa":true,"landing_page_url":"http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-137896","pdf_url":null,"source":{"id":"https://openalex.org/S4306400838","display_name":"DiVA (Linkoping University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/conferenceObject"},"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.7099999785423279}],"awards":[],"funders":[{"id":"https://openalex.org/F4320309480","display_name":"Nvidia","ror":"https://ror.org/03jdj4y14"},{"id":"https://openalex.org/F4320321040","display_name":"National Science Council","ror":"https://ror.org/02kv4zf79"},{"id":"https://openalex.org/F4320321551","display_name":"Chongqing University of Arts and Sciences","ror":"https://ror.org/01rcvq140"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":52,"referenced_works":["https://openalex.org/W24089286","https://openalex.org/W161114242","https://openalex.org/W182940129","https://openalex.org/W818325216","https://openalex.org/W823292820","https://openalex.org/W1686810756","https://openalex.org/W1744759976","https://openalex.org/W1857884451","https://openalex.org/W1867429401","https://openalex.org/W1892578678","https://openalex.org/W1904671147","https://openalex.org/W1909952827","https://openalex.org/W1923332106","https://openalex.org/W1955514522","https://openalex.org/W1955741794","https://openalex.org/W1960777822","https://openalex.org/W1964846093","https://openalex.org/W1997121481","https://openalex.org/W2044986361","https://openalex.org/W2062118960","https://openalex.org/W2089961441","https://openalex.org/W2098941887","https://openalex.org/W2099427078","https://openalex.org/W2117539524","https://openalex.org/W2130026429","https://openalex.org/W2140595412","https://openalex.org/W2149829493","https://openalex.org/W2154429285","https://openalex.org/W2154889144","https://openalex.org/W2156303437","https://openalex.org/W2158592639","https://openalex.org/W2161381512","https://openalex.org/W2168356304","https://openalex.org/W2186330282","https://openalex.org/W2214352687","https://openalex.org/W2244956674","https://openalex.org/W2469582947","https://openalex.org/W2518013266","https://openalex.org/W2962835968","https://openalex.org/W3102624093","https://openalex.org/W6600983433","https://openalex.org/W6606595081","https://openalex.org/W6607635097","https://openalex.org/W6623108133","https://openalex.org/W6623482698","https://openalex.org/W6637373629","https://openalex.org/W6639126518","https://openalex.org/W6649598916","https://openalex.org/W6679027886","https://openalex.org/W6682864246","https://openalex.org/W6691023176","https://openalex.org/W6726293469"],"related_works":["https://openalex.org/W2772917594","https://openalex.org/W2036807459","https://openalex.org/W2058170566","https://openalex.org/W2755342338","https://openalex.org/W2166024367","https://openalex.org/W3116076068","https://openalex.org/W2229312674","https://openalex.org/W2951359407","https://openalex.org/W2079911747","https://openalex.org/W1969923398"],"abstract_inverted_index":{"Robust":[0],"visual":[1,68,155],"tracking":[2,64],"is":[3],"a":[4,92,118],"challenging":[5],"computer":[6],"vision":[7],"problem,":[8],"with":[9,150,165],"many":[10],"real-world":[11],"applications.":[12],"Most":[13],"existing":[14],"approaches":[15],"employ":[16],"hand-crafted":[17],"appearance":[18,48,148,174],"features,":[19],"such":[20],"as":[21],"HOG":[22],"or":[23],"Color":[24],"Names.":[25],"Recently,":[26],"deep":[27,70,114,126,129,151,166],"RGB":[28],"features":[29,45,72,87,116,131,153,168],"extracted":[30,98],"from":[31,99],"convolutional":[32],"neural":[33],"networks":[34],"have":[35,73],"been":[36,74],"successfully":[37,75],"applied":[38,76],"for":[39,77,154],"tracking.":[40,156],"Despite":[41],"their":[42],"success,":[43],"these":[44],"only":[46],"capture":[47],"information.":[49,134],"On":[50],"the":[51,85,111,136,143],"other":[52],"hand,":[53],"motion":[54,71,86,115,130,152,167],"cues":[55],"provide":[56],"discriminative":[57],"and":[58,80,128],"complementary":[59,133],"information":[60,149,175],"that":[61,124,161],"can":[62],"improve":[63],"performance.":[65],"Contrary":[66],"to":[67,145],"tracking,":[69],"action":[78],"recognition":[79],"video":[81],"classification":[82],"tasks.":[83],"Typically,":[84],"are":[88,142],"learned":[89],"by":[90],"training":[91],"CNN":[93],"on":[94,173],"optical":[95],"flow":[96],"images":[97],"large":[100],"amounts":[101],"of":[102,110,113,138],"labeled":[103],"videos.":[104],"This":[105],"paper":[106],"presents":[107],"an":[108],"investigation":[109],"impact":[112],"in":[117],"tracking-by-detection":[119],"framework.":[120],"We":[121],"further":[122],"show":[123],"hand-crafted,":[125],"RGB,":[127],"contain":[132],"To":[135],"best":[137],"our":[139,162],"knowledge,":[140],"we":[141],"first":[144],"propose":[146],"fusing":[147],"Comprehensive":[157],"experiments":[158],"clearly":[159],"suggest":[160],"fusion":[163],"approach":[164],"outperforms":[169],"standard":[170],"methods":[171],"relying":[172],"alone.":[176]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":11},{"year":2021,"cited_by_count":14},{"year":2020,"cited_by_count":21},{"year":2019,"cited_by_count":11},{"year":2018,"cited_by_count":15},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}