{"id":"https://openalex.org/W2773592164","doi":"https://doi.org/10.1109/iccais.2017.8217574","title":"Deep neural network for person re-identification in a non-overlapping camera network","display_name":"Deep neural network for person re-identification in a non-overlapping camera network","publication_year":2017,"publication_date":"2017-10-01","ids":{"openalex":"https://openalex.org/W2773592164","doi":"https://doi.org/10.1109/iccais.2017.8217574","mag":"2773592164"},"language":"en","primary_location":{"id":"doi:10.1109/iccais.2017.8217574","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccais.2017.8217574","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 Control, Automation and Information Sciences (ICCAIS)","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/A5075566234","display_name":"Hyunguk Choi","orcid":"https://orcid.org/0000-0002-5277-6113"},"institutions":[{"id":"https://openalex.org/I39534123","display_name":"Gwangju Institute of Science and Technology","ror":"https://ror.org/024kbgz78","country_code":"KR","type":"education","lineage":["https://openalex.org/I39534123"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Hyunguk Choi","raw_affiliation_strings":["School of Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology, Gwangju, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology, Gwangju, Republic of Korea","institution_ids":["https://openalex.org/I39534123"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5056743652","display_name":"Moongu Jeon","orcid":"https://orcid.org/0000-0002-2775-7789"},"institutions":[{"id":"https://openalex.org/I39534123","display_name":"Gwangju Institute of Science and Technology","ror":"https://ror.org/024kbgz78","country_code":"KR","type":"education","lineage":["https://openalex.org/I39534123"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Moongu Jeon","raw_affiliation_strings":["School of Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology, Gwangju, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology, Gwangju, Republic of Korea","institution_ids":["https://openalex.org/I39534123"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5075566234"],"corresponding_institution_ids":["https://openalex.org/I39534123"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.18124117,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"18","issue":null,"first_page":"193","last_page":"196"},"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/T11448","display_name":"Face recognition and analysis","score":0.9983999729156494,"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/T12740","display_name":"Gait Recognition and Analysis","score":0.9951000213623047,"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/kernel","display_name":"Kernel (algebra)","score":0.7257435321807861},{"id":"https://openalex.org/keywords/salient","display_name":"Salient","score":0.7109562754631042},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7050299644470215},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6991091966629028},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6918936967849731},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.6819913387298584},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.665549635887146},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6322324872016907},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5117763876914978},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.503429114818573},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.4291994571685791},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.42752042412757874},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4128096103668213},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.39389240741729736},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.17270898818969727}],"concepts":[{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.7257435321807861},{"id":"https://openalex.org/C2780719617","wikidata":"https://www.wikidata.org/wiki/Q1030752","display_name":"Salient","level":2,"score":0.7109562754631042},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7050299644470215},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6991091966629028},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6918936967849731},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.6819913387298584},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.665549635887146},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6322324872016907},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5117763876914978},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.503429114818573},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.4291994571685791},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.42752042412757874},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4128096103668213},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.39389240741729736},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.17270898818969727},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","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/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iccais.2017.8217574","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccais.2017.8217574","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 Control, Automation and Information Sciences (ICCAIS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W1518138188","https://openalex.org/W1522301498","https://openalex.org/W1533861849","https://openalex.org/W1602182271","https://openalex.org/W1928419358","https://openalex.org/W1979260620","https://openalex.org/W1982925187","https://openalex.org/W2042436258","https://openalex.org/W2068042582","https://openalex.org/W2109824782","https://openalex.org/W2114694114","https://openalex.org/W2125889200","https://openalex.org/W2130556178","https://openalex.org/W2135442311","https://openalex.org/W2140157192","https://openalex.org/W2158139921","https://openalex.org/W2346749775","https://openalex.org/W2491664569","https://openalex.org/W2957055540","https://openalex.org/W2964121744","https://openalex.org/W6631190155","https://openalex.org/W6631943919","https://openalex.org/W6636160605","https://openalex.org/W6675751002","https://openalex.org/W6683338658","https://openalex.org/W6722869231","https://openalex.org/W6765813093"],"related_works":["https://openalex.org/W2329500892","https://openalex.org/W28991112","https://openalex.org/W2370726991","https://openalex.org/W2369710579","https://openalex.org/W4327728159","https://openalex.org/W4394266730","https://openalex.org/W4388913932","https://openalex.org/W4309130263","https://openalex.org/W2138022083","https://openalex.org/W4292523377"],"abstract_inverted_index":{"Person":[0],"re-identification":[1,19],"is":[2],"important":[3],"and":[4,33],"challenging":[5,120],"parts":[6],"in":[7,110],"a":[8,103,108],"non-overlapping":[9],"camera":[10],"network.":[11],"In":[12],"this":[13],"paper,":[14],"we":[15],"propose":[16],"the":[17,30,38,52,65,90],"person":[18,31],"framework":[20,45,115],"which":[21,106],"consists":[22],"of":[23,75,88,92],"kernel":[24,60],"size":[25,61],"into":[26],"convolutional":[27],"layers":[28],"considering":[29],"ratio":[32],"relationship":[34,39,104],"matrix":[35,105],"that":[36],"train":[37],"information":[40,86],"related":[41],"to":[42,64,83,101],"neighborhoods.":[43],"Our":[44,113],"deals":[46],"with":[47],"global":[48],"feature":[49,77],"extracted":[50,78,95],"from":[51,79],"whole":[53],"body.":[54],"The":[55,73,94],"features":[56,96],"generated":[57],"by":[58,69],"suitable":[59],"are":[62,97],"different":[63],"local":[66,76],"featured":[67],"making":[68],"separated":[70],"body":[71],"images.":[72],"approaches":[74],"divided":[80],"bodies":[81],"tend":[82],"lose":[84],"salient":[85],"because":[87],"cutting":[89],"characteristic":[91],"products.":[93],"used":[98],"as":[99],"elements":[100],"learn":[102],"plays":[107],"role":[109],"distinction":[111],"function.":[112],"proposed":[114],"outperforms":[116],"state-of-the-art":[117],"methods":[118],"on":[119],"datasets.":[121]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
