{"id":"https://openalex.org/W2767557714","doi":"https://doi.org/10.1109/icdsp.2017.8096040","title":"Bi-directional superpixel earth mover's distance for training free person re-identification","display_name":"Bi-directional superpixel earth mover's distance for training free person re-identification","publication_year":2017,"publication_date":"2017-08-01","ids":{"openalex":"https://openalex.org/W2767557714","doi":"https://doi.org/10.1109/icdsp.2017.8096040","mag":"2767557714"},"language":"en","primary_location":{"id":"doi:10.1109/icdsp.2017.8096040","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icdsp.2017.8096040","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 22nd International Conference on Digital Signal Processing (DSP)","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/A5100769643","display_name":"Chong Wang","orcid":"https://orcid.org/0000-0001-6016-6545"},"institutions":[{"id":"https://openalex.org/I109935558","display_name":"Ningbo University","ror":"https://ror.org/03et85d35","country_code":"CN","type":"education","lineage":["https://openalex.org/I109935558"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Chong Wang","raw_affiliation_strings":["Dept. of Electrical Engineering & Computer Science, Ningbo University, Ningbo, P. R. China"],"affiliations":[{"raw_affiliation_string":"Dept. of Electrical Engineering & Computer Science, Ningbo University, Ningbo, P. R. China","institution_ids":["https://openalex.org/I109935558"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102174961","display_name":"Zhouchi Lin","orcid":null},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]},{"id":"https://openalex.org/I200769079","display_name":"Hong Kong University of Science and Technology","ror":"https://ror.org/00q4vv597","country_code":"HK","type":"education","lineage":["https://openalex.org/I200769079"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Zhouchi Lin","raw_affiliation_strings":["Department of Electrical & Electronic Engineering, The University of Hong Kong, Hong kong"],"affiliations":[{"raw_affiliation_string":"Department of Electrical & Electronic Engineering, The University of Hong Kong, Hong kong","institution_ids":["https://openalex.org/I200769079","https://openalex.org/I889458895"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5057049452","display_name":"S. C. Chan","orcid":"https://orcid.org/0000-0001-7212-4182"},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]},{"id":"https://openalex.org/I200769079","display_name":"Hong Kong University of Science and Technology","ror":"https://ror.org/00q4vv597","country_code":"HK","type":"education","lineage":["https://openalex.org/I200769079"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Shing-Chow Chan","raw_affiliation_strings":["Department of Electrical & Electronic Engineering, The University of Hong Kong, Hong kong"],"affiliations":[{"raw_affiliation_string":"Department of Electrical & Electronic Engineering, The University of Hong Kong, Hong kong","institution_ids":["https://openalex.org/I200769079","https://openalex.org/I889458895"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100769643"],"corresponding_institution_ids":["https://openalex.org/I109935558"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.15937458,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"3","issue":null,"first_page":"1","last_page":"5"},"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":0.995199978351593,"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/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9904999732971191,"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/earth-movers-distance","display_name":"Earth mover's distance","score":0.7370672225952148},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7185143232345581},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.6868861317634583},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6819353103637695},{"id":"https://openalex.org/keywords/scheme","display_name":"Scheme (mathematics)","score":0.6735981702804565},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.6483452320098877},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.5942100286483765},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5136587023735046},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.4844827353954315},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.45273274183273315},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.4191851317882538},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14276909828186035},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.05930158495903015}],"concepts":[{"id":"https://openalex.org/C82668687","wikidata":"https://www.wikidata.org/wiki/Q3046456","display_name":"Earth mover's distance","level":2,"score":0.7370672225952148},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7185143232345581},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.6868861317634583},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6819353103637695},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.6735981702804565},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.6483452320098877},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.5942100286483765},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5136587023735046},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.4844827353954315},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.45273274183273315},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.4191851317882538},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14276909828186035},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.05930158495903015},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icdsp.2017.8096040","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icdsp.2017.8096040","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 22nd International Conference on Digital Signal Processing (DSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","score":0.5600000023841858,"display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W41482161","https://openalex.org/W1518138188","https://openalex.org/W1602182271","https://openalex.org/W1949591461","https://openalex.org/W1982925187","https://openalex.org/W1985891935","https://openalex.org/W2029287185","https://openalex.org/W2041719651","https://openalex.org/W2046835352","https://openalex.org/W2048110836","https://openalex.org/W2068042582","https://openalex.org/W2071631792","https://openalex.org/W2079972027","https://openalex.org/W2089074647","https://openalex.org/W2098807270","https://openalex.org/W2109824782","https://openalex.org/W2113609219","https://openalex.org/W2118246710","https://openalex.org/W2130556178","https://openalex.org/W2169495281","https://openalex.org/W2441160157","https://openalex.org/W6601733005","https://openalex.org/W6631178364","https://openalex.org/W6636160605","https://openalex.org/W6674809736","https://openalex.org/W6675751002","https://openalex.org/W6718643136"],"related_works":["https://openalex.org/W2015573458","https://openalex.org/W2113049000","https://openalex.org/W2125221595","https://openalex.org/W1540114044","https://openalex.org/W1971648542","https://openalex.org/W2516227785","https://openalex.org/W2128528962","https://openalex.org/W333414154","https://openalex.org/W2049988766","https://openalex.org/W2132438428"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3],"propose":[4],"a":[5,61],"new":[6],"person":[7,89,99],"re-identification":[8,100],"algorithm":[9,68],"based":[10,31,107],"on":[11,32,53],"bi-directional":[12,39],"superpixel":[13],"earth":[14],"mover's":[15],"distance":[16],"(BD-SP-EMD).":[17],"To":[18],"address":[19],"the":[20,24,46,66,72,94,97],"viewpoint":[21],"change":[22],"issue,":[23],"human":[25],"body":[26],"segmentation":[27],"is":[28,41,82,102],"first":[29],"extracted":[30],"background":[33],"modeling":[34],"and":[35,48],"saliency":[36],"maps.":[37],"A":[38],"scheme":[40],"then":[42],"applied":[43],"to":[44],"obtain":[45],"forward":[47],"backward":[49],"SP-EMD":[50],"distances.":[51],"Based":[52],"these":[54],"two":[55,77,87],"distances,":[56],"pedestrians":[57],"are":[58],"re-identified":[59],"by":[60],"two-step":[62],"ranking":[63],"scheme.":[64],"Since":[65],"proposed":[67,98],"can":[69],"directly":[70],"calculate":[71],"dissimilarity":[73],"between":[74],"any":[75],"given":[76],"images,":[78],"no":[79],"training":[80,106],"data":[81],"required.":[83],"Experimental":[84],"results":[85],"using":[86],"public":[88],"re-id":[90],"datasets":[91],"show":[92],"that":[93],"performance":[95],"of":[96],"method":[101],"comparable":[103],"with":[104],"other":[105],"algorithms.":[108]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
