{"id":"https://openalex.org/W2166135900","doi":"https://doi.org/10.1109/tpami.2014.2360689","title":"Boundary Preserving Dense Local Regions","display_name":"Boundary Preserving Dense Local Regions","publication_year":2014,"publication_date":"2014-09-29","ids":{"openalex":"https://openalex.org/W2166135900","doi":"https://doi.org/10.1109/tpami.2014.2360689","mag":"2166135900","pmid":"https://pubmed.ncbi.nlm.nih.gov/26353319"},"language":"en","primary_location":{"id":"doi:10.1109/tpami.2014.2360689","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2014.2360689","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5073472506","display_name":"Jaechul Kim","orcid":null},"institutions":[{"id":"https://openalex.org/I4210089985","display_name":"Amazon (Germany)","ror":"https://ror.org/00b9ktm87","country_code":"DE","type":"company","lineage":["https://openalex.org/I1311688040","https://openalex.org/I4210089985"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Jaechul Kim","raw_affiliation_strings":["Amazon"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Amazon","institution_ids":["https://openalex.org/I4210089985"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5012765543","display_name":"Kristen Grauman","orcid":"https://orcid.org/0000-0002-9591-5873"},"institutions":[{"id":"https://openalex.org/I86519309","display_name":"The University of Texas at Austin","ror":"https://ror.org/00hj54h04","country_code":"US","type":"education","lineage":["https://openalex.org/I86519309"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kristen Grauman","raw_affiliation_strings":["Department of Computer Science, University of Texas at Austin, 1 University Station, TX, Austin"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Texas at Austin, 1 University Station, TX, Austin","institution_ids":["https://openalex.org/I86519309"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.2426,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.62133127,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"37","issue":"5","first_page":"931","last_page":"943"},"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":0.9998999834060669,"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":0.9998999834060669,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9993000030517578,"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":0.9993000030517578,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.8009049892425537},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7341976761817932},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.6491934061050415},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6480481624603271},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6237354874610901},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6188973784446716},{"id":"https://openalex.org/keywords/boundary","display_name":"Boundary (topology)","score":0.5964407324790955},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5951996445655823},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5684471726417542},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.5649434328079224},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5277688503265381},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5001134872436523},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.48896872997283936},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.468898206949234},{"id":"https://openalex.org/keywords/cognitive-neuroscience-of-visual-object-recognition","display_name":"Cognitive neuroscience of visual object recognition","score":0.4630707800388336},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.43115097284317017},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2857248783111572},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.065367192029953}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8009049892425537},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7341976761817932},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.6491934061050415},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6480481624603271},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6237354874610901},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6188973784446716},{"id":"https://openalex.org/C62354387","wikidata":"https://www.wikidata.org/wiki/Q875399","display_name":"Boundary (topology)","level":2,"score":0.5964407324790955},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5951996445655823},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5684471726417542},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.5649434328079224},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5277688503265381},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5001134872436523},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.48896872997283936},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.468898206949234},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.4630707800388336},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.43115097284317017},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2857248783111572},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.065367192029953},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","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/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"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/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tpami.2014.2360689","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2014.2360689","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},{"id":"pmid:26353319","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/26353319","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on pattern analysis and machine intelligence","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G7453056415","display_name":null,"funder_award_id":"N00014-12-1-0068","funder_id":"https://openalex.org/F4320337345","funder_display_name":"Office of Naval Research"}],"funders":[{"id":"https://openalex.org/F4320310620","display_name":"University of Texas at Austin","ror":"https://ror.org/00hj54h04"},{"id":"https://openalex.org/F4320337345","display_name":"Office of Naval Research","ror":"https://ror.org/00rk2pe57"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":53,"referenced_works":["https://openalex.org/W1501467284","https://openalex.org/W1570918423","https://openalex.org/W1919689106","https://openalex.org/W1980911747","https://openalex.org/W1983254201","https://openalex.org/W1989348325","https://openalex.org/W1999478155","https://openalex.org/W2009685382","https://openalex.org/W2044373869","https://openalex.org/W2103897297","https://openalex.org/W2104125540","https://openalex.org/W2104978738","https://openalex.org/W2110158442","https://openalex.org/W2114766304","https://openalex.org/W2116046277","https://openalex.org/W2117030034","https://openalex.org/W2117132237","https://openalex.org/W2122808326","https://openalex.org/W2124351162","https://openalex.org/W2124861766","https://openalex.org/W2125849446","https://openalex.org/W2129004009","https://openalex.org/W2129156852","https://openalex.org/W2129305389","https://openalex.org/W2137218141","https://openalex.org/W2140726582","https://openalex.org/W2143343451","https://openalex.org/W2146307402","https://openalex.org/W2147237076","https://openalex.org/W2154583877","https://openalex.org/W2154683974","https://openalex.org/W2155979701","https://openalex.org/W2158911526","https://openalex.org/W2162915993","https://openalex.org/W2163267793","https://openalex.org/W2165084023","https://openalex.org/W2165828254","https://openalex.org/W2166742463","https://openalex.org/W2166820607","https://openalex.org/W2168002178","https://openalex.org/W2171896402","https://openalex.org/W2172188317","https://openalex.org/W2537310184","https://openalex.org/W2606668424","https://openalex.org/W4248635988","https://openalex.org/W6629747462","https://openalex.org/W6634175034","https://openalex.org/W6639956668","https://openalex.org/W6675696854","https://openalex.org/W6677634198","https://openalex.org/W6678684981","https://openalex.org/W6684893555","https://openalex.org/W6685292306"],"related_works":["https://openalex.org/W2378211422","https://openalex.org/W2745001401","https://openalex.org/W4321353415","https://openalex.org/W2130974462","https://openalex.org/W972276598","https://openalex.org/W4246352526","https://openalex.org/W2028665553","https://openalex.org/W4287991909","https://openalex.org/W4390721878","https://openalex.org/W4387272257"],"abstract_inverted_index":{"We":[0],"propose":[1],"a":[2],"dense":[3,72],"local":[4,20],"region":[5,89],"detector":[6,90],"to":[7,60,69,102,116],"extract":[8],"features":[9],"suitable":[10],"for":[11,98],"image":[12],"matching":[13,100],"and":[14,43,48,63,74,95,132],"object":[15,30,46,64,99,135],"recognition":[16],"tasks.":[17],"Whereas":[18],"traditional":[19],"interest":[21],"operators":[22],"rely":[23],"on":[24,119],"repeatable":[25],"structures":[26],"that":[27,86,123],"often":[28],"cross":[29],"boundaries":[31,47],"(e.g.,":[32],"corners,":[33],"scale-space":[34],"blobs),":[35],"our":[36,66,113],"sampling":[37],"strategy":[38],"is":[39],"driven":[40],"by":[41],"segmentation,":[42],"thus":[44],"preserves":[45],"shape.":[49],"At":[50],"the":[51,87],"same":[52],"time,":[53],"whereas":[54],"existing":[55,106],"region-based":[56],"representations":[57],"are":[58],"sensitive":[59],"segmentation":[61],"parameters":[62],"deformations,":[65],"novel":[67],"approach":[68],"robustly":[70],"sample":[71],"sites":[73],"determine":[75],"their":[76],"connectivity":[77],"offers":[78],"better":[79,93],"repeatability.":[80],"In":[81,109],"extensive":[82],"experiments,":[83],"we":[84,111],"find":[85],"proposed":[88],"provides":[91],"significantly":[92],"repeatability":[94],"localization":[96],"accuracy":[97],"compared":[101],"an":[103],"array":[104],"of":[105],"feature":[107,126],"detectors.":[108],"addition,":[110],"show":[112],"regions":[114],"lead":[115],"excellent":[117],"results":[118],"two":[120],"benchmark":[121],"tasks":[122],"require":[124],"good":[125],"matching:":[127],"weakly":[128],"supervised":[129],"foreground":[130],"discovery":[131],"nearest":[133],"neighbor-based":[134],"recognition.":[136]},"counts_by_year":[{"year":2020,"cited_by_count":1},{"year":2018,"cited_by_count":2},{"year":2015,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
