{"id":"https://openalex.org/W2008056457","doi":"https://doi.org/10.1109/icip.2013.6738530","title":"A novel pair-wise image matching strategy with compact descriptors","display_name":"A novel pair-wise image matching strategy with compact descriptors","publication_year":2013,"publication_date":"2013-09-01","ids":{"openalex":"https://openalex.org/W2008056457","doi":"https://doi.org/10.1109/icip.2013.6738530","mag":"2008056457"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2013.6738530","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2013.6738530","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE International Conference on Image Processing","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/A5020086523","display_name":"Shuang Yang","orcid":"https://orcid.org/0000-0003-1133-384X"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Shuang Yang","raw_affiliation_strings":["The Institute of Digital Media, School of CS & EE, Peking University, Beijing 100871, China","Sch. of CS & EE, Peking Univ., Beijing, China"],"affiliations":[{"raw_affiliation_string":"The Institute of Digital Media, School of CS & EE, Peking University, Beijing 100871, China","institution_ids":["https://openalex.org/I20231570"]},{"raw_affiliation_string":"Sch. of CS & EE, Peking Univ., Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024879728","display_name":"Ling\u2010Yu Duan","orcid":"https://orcid.org/0000-0002-4491-2023"},"institutions":[{"id":"https://openalex.org/I4210128628","display_name":"Peking University Shenzhen Hospital","ror":"https://ror.org/03kkjyb15","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210128628"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ling-Yu Duan","raw_affiliation_strings":["Shenzhen Graduate School, Peking University, Shenzhen 518055, China","Shenzhen Grad. Sch., Peking Univ., Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Shenzhen Graduate School, Peking University, Shenzhen 518055, China","institution_ids":["https://openalex.org/I4210128628"]},{"raw_affiliation_string":"Shenzhen Grad. Sch., Peking Univ., Shenzhen, China","institution_ids":["https://openalex.org/I4210128628"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101810781","display_name":"Jie Lin","orcid":"https://orcid.org/0000-0002-1689-522X"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Lin","raw_affiliation_strings":["The Institute of Digital Media, School of CS & EE, Peking University, Beijing 100871, China","Sch. of CS & EE, Peking Univ., Beijing, China"],"affiliations":[{"raw_affiliation_string":"The Institute of Digital Media, School of CS & EE, Peking University, Beijing 100871, China","institution_ids":["https://openalex.org/I20231570"]},{"raw_affiliation_string":"Sch. of CS & EE, Peking Univ., Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5058066577","display_name":"Tiejun Huang","orcid":"https://orcid.org/0000-0002-4234-6099"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tiejun Huang","raw_affiliation_strings":["The Institute of Digital Media, School of CS & EE, Peking University, Beijing 100871, China","Sch. of CS & EE, Peking Univ., Beijing, China"],"affiliations":[{"raw_affiliation_string":"The Institute of Digital Media, School of CS & EE, Peking University, Beijing 100871, China","institution_ids":["https://openalex.org/I20231570"]},{"raw_affiliation_string":"Sch. of CS & EE, Peking Univ., Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5020086523"],"corresponding_institution_ids":["https://openalex.org/I20231570"],"apc_list":null,"apc_paid":null,"fwci":0.2722,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.58149042,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"2572","last_page":"2576"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9983999729156494,"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"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9871000051498413,"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/scale-invariant-feature-transform","display_name":"Scale-invariant feature transform","score":0.7292170524597168},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6630415320396423},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6568719744682312},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.6407324075698853},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6009101271629333},{"id":"https://openalex.org/keywords/quantization","display_name":"Quantization (signal processing)","score":0.5574023127555847},{"id":"https://openalex.org/keywords/vector-quantization","display_name":"Vector quantization","score":0.4338221848011017},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4212706983089447},{"id":"https://openalex.org/keywords/image-matching","display_name":"Image matching","score":0.41612082719802856},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.36576369404792786},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2761107087135315}],"concepts":[{"id":"https://openalex.org/C61265191","wikidata":"https://www.wikidata.org/wiki/Q767770","display_name":"Scale-invariant feature transform","level":3,"score":0.7292170524597168},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6630415320396423},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6568719744682312},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.6407324075698853},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6009101271629333},{"id":"https://openalex.org/C28855332","wikidata":"https://www.wikidata.org/wiki/Q198099","display_name":"Quantization (signal processing)","level":2,"score":0.5574023127555847},{"id":"https://openalex.org/C199833920","wikidata":"https://www.wikidata.org/wiki/Q612536","display_name":"Vector quantization","level":2,"score":0.4338221848011017},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4212706983089447},{"id":"https://openalex.org/C2986492983","wikidata":"https://www.wikidata.org/wiki/Q861092","display_name":"Image matching","level":3,"score":0.41612082719802856},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.36576369404792786},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2761107087135315},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip.2013.6738530","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2013.6738530","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE International Conference on Image Processing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5,"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W1491719799","https://openalex.org/W1566135517","https://openalex.org/W1677409904","https://openalex.org/W1995922888","https://openalex.org/W2006002369","https://openalex.org/W2012592962","https://openalex.org/W2061458817","https://openalex.org/W2069463273","https://openalex.org/W2071027807","https://openalex.org/W2108444897","https://openalex.org/W2119605622","https://openalex.org/W2125378448","https://openalex.org/W2128017662","https://openalex.org/W2131846894","https://openalex.org/W2147238549","https://openalex.org/W2150782236","https://openalex.org/W2151103935","https://openalex.org/W2157941578","https://openalex.org/W2166473218","https://openalex.org/W2177274842","https://openalex.org/W2293597654","https://openalex.org/W2295033550","https://openalex.org/W6629564929","https://openalex.org/W6651739055","https://openalex.org/W6668250444","https://openalex.org/W6676079856","https://openalex.org/W6678556256","https://openalex.org/W6684116732","https://openalex.org/W6697214482","https://openalex.org/W6697444687"],"related_works":["https://openalex.org/W2121067345","https://openalex.org/W3209251257","https://openalex.org/W4206457185","https://openalex.org/W2791375867","https://openalex.org/W2060133567","https://openalex.org/W2360960220","https://openalex.org/W2163812102","https://openalex.org/W2374700396","https://openalex.org/W2120321595","https://openalex.org/W2617958085"],"abstract_inverted_index":{"In":[0],"this":[1,33,77],"paper,":[2],"we":[3,96,119],"address":[4],"the":[5,17,27,38,92,114,133,143],"problem":[6,57],"of":[7,91,117],"pair-wise":[8],"image":[9,49],"matching":[10,25,109,134,151],"which":[11],"determines":[12],"whether":[13],"two":[14],"images":[15,87],"depict":[16],"same":[18,93],"objects":[19,90],"or":[20],"scenes.":[21],"SIFT-like":[22],"local":[23,42,54,103],"descriptor-based":[24,43],"is":[26,80],"most":[28],"widely":[29],"adopted":[30],"method":[31],"for":[32,82,107],"purpose":[34],"and":[35,66,104,123,130,153],"has":[36],"achieved":[37],"state-of-the-art":[39,144],"performance.":[40],"However,":[41],"methods":[44,145],"usually":[45],"fail":[46],"when":[47,61],"an":[48],"pair":[50],"contains":[51],"multiple":[52],"similar":[53],"regions.":[55],"This":[56],"becomes":[58],"more":[59],"serious":[60],"coming":[62],"to":[63,85,101,126,142],"limited":[64],"computational":[65],"storage":[67],"resources.":[68],"Although":[69],"global":[70,83,105],"descriptors,":[71],"e.g.,":[72],"Fisher":[73],"Vectors,":[74],"can":[75],"solve":[76],"issue,":[78],"it":[79],"difficult":[81],"descriptors":[84,106,129],"distinguish":[86],"containing":[88],"different":[89],"class.":[94],"Therefore,":[95],"propose":[97],"a":[98],"novel":[99],"strategy":[100],"integrate":[102],"better":[108],"accuracy.":[110],"To":[111],"further":[112],"fulfill":[113],"efficiency":[115],"requirement":[116],"applications,":[118],"combine":[120],"dimension":[121],"reduction":[122],"product":[124],"quantization":[125],"obtain":[127],"compact":[128],"speed":[131],"up":[132],"process":[135],"with":[136],"pre-computed":[137],"lookup":[138],"tables.":[139],"Extensive":[140],"comparisons":[141],"demonstrate":[146],"our":[147],"advantages":[148],"in":[149],"both":[150],"accuracy":[152],"efficiency.":[154]},"counts_by_year":[{"year":2015,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}