{"id":"https://openalex.org/W2055527244","doi":"https://doi.org/10.1109/cvpr.2010.5539907","title":"Food recognition using statistics of pairwise local features","display_name":"Food recognition using statistics of pairwise local features","publication_year":2010,"publication_date":"2010-06-01","ids":{"openalex":"https://openalex.org/W2055527244","doi":"https://doi.org/10.1109/cvpr.2010.5539907","mag":"2055527244"},"language":"en","primary_location":{"id":"doi:10.1109/cvpr.2010.5539907","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2010.5539907","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition","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/A5009052681","display_name":"Shulin Yang","orcid":"https://orcid.org/0000-0002-9186-4415"},"institutions":[{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Shulin Yang","raw_affiliation_strings":["University of Washington, USA"],"affiliations":[{"raw_affiliation_string":"University of Washington, USA","institution_ids":["https://openalex.org/I201448701"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101826256","display_name":"Mei Chen","orcid":"https://orcid.org/0000-0002-5309-136X"},"institutions":[{"id":"https://openalex.org/I1343180700","display_name":"Intel (United States)","ror":"https://ror.org/01ek73717","country_code":"US","type":"company","lineage":["https://openalex.org/I1343180700"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mei Chen","raw_affiliation_strings":["INTEL, Research Laboratory, USA"],"affiliations":[{"raw_affiliation_string":"INTEL, Research Laboratory, USA","institution_ids":["https://openalex.org/I1343180700"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075354321","display_name":"Dean Pomerleau","orcid":null},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]},{"id":"https://openalex.org/I1343180700","display_name":"Intel (United States)","ror":"https://ror.org/01ek73717","country_code":"US","type":"company","lineage":["https://openalex.org/I1343180700"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"D Pomerleau","raw_affiliation_strings":["INTEL, Research Laboratory, USA","Robotics Institute, Carnegie Mellon University, USA"],"affiliations":[{"raw_affiliation_string":"INTEL, Research Laboratory, USA","institution_ids":["https://openalex.org/I1343180700"]},{"raw_affiliation_string":"Robotics Institute, Carnegie Mellon University, USA","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5066107323","display_name":"Rahul Sukthankar","orcid":null},"institutions":[{"id":"https://openalex.org/I1343180700","display_name":"Intel (United States)","ror":"https://ror.org/01ek73717","country_code":"US","type":"company","lineage":["https://openalex.org/I1343180700"]},{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"R Sukthankar","raw_affiliation_strings":["INTEL, Research Laboratory, USA","Robotics Institute, Carnegie Mellon University, USA"],"affiliations":[{"raw_affiliation_string":"INTEL, Research Laboratory, USA","institution_ids":["https://openalex.org/I1343180700"]},{"raw_affiliation_string":"Robotics Institute, Carnegie Mellon University, USA","institution_ids":["https://openalex.org/I74973139"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5009052681"],"corresponding_institution_ids":["https://openalex.org/I201448701"],"apc_list":null,"apc_paid":null,"fwci":6.9556,"has_fulltext":false,"cited_by_count":269,"citation_normalized_percentile":{"value":0.97326924,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"2249","last_page":"2256"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11667","display_name":"Advanced Chemical Sensor Technologies","score":0.9979000091552734,"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"}},"topics":[{"id":"https://openalex.org/T11667","display_name":"Advanced Chemical Sensor Technologies","score":0.9979000091552734,"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"}},{"id":"https://openalex.org/T12388","display_name":"Identification and Quantification in Food","score":0.9685999751091003,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9682000279426575,"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/discriminative-model","display_name":"Discriminative model","score":0.7816544771194458},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7797255516052246},{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.7657684087753296},{"id":"https://openalex.org/keywords/pairwise-comparison","display_name":"Pairwise comparison","score":0.7224968075752258},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7150096893310547},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6389316320419312},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5758652091026306},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.5284103155136108},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.49867773056030273},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.41077175736427307},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2514845132827759}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.7816544771194458},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7797255516052246},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.7657684087753296},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.7224968075752258},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7150096893310547},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6389316320419312},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5758652091026306},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.5284103155136108},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.49867773056030273},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.41077175736427307},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2514845132827759},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cvpr.2010.5539907","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2010.5539907","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.6000000238418579}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1505571759","https://openalex.org/W1553558465","https://openalex.org/W1566135517","https://openalex.org/W1669678558","https://openalex.org/W1958762911","https://openalex.org/W2089439257","https://openalex.org/W2096761622","https://openalex.org/W2100588357","https://openalex.org/W2105872016","https://openalex.org/W2108444897","https://openalex.org/W2133777675","https://openalex.org/W2135884851","https://openalex.org/W2149445327","https://openalex.org/W2151103935","https://openalex.org/W2153635508","https://openalex.org/W2157084238","https://openalex.org/W2164877691","https://openalex.org/W2173414649","https://openalex.org/W2543791385","https://openalex.org/W2601795100","https://openalex.org/W3120421331","https://openalex.org/W4285719527","https://openalex.org/W6633294049","https://openalex.org/W6641096339","https://openalex.org/W6672807307","https://openalex.org/W6676062317","https://openalex.org/W6676079856","https://openalex.org/W6682343485","https://openalex.org/W6683978607"],"related_works":["https://openalex.org/W17155033","https://openalex.org/W3207760230","https://openalex.org/W1496222301","https://openalex.org/W1590307681","https://openalex.org/W2536018345","https://openalex.org/W4312814274","https://openalex.org/W4285370786","https://openalex.org/W2296488620","https://openalex.org/W2358353312","https://openalex.org/W1487808658"],"abstract_inverted_index":{"Food":[0],"recognition":[1],"is":[2,23,77,95],"difficult":[3],"because":[4],"food":[5,22,46,101],"items":[6,47],"are":[7],"de-formable":[8],"objects":[9],"that":[10,48,91],"exhibit":[11],"significant":[12],"variations":[13],"in":[14,37,72],"appearance.":[15],"We":[16,40,68],"believe":[17],"the":[18,26,62,92],"key":[19],"to":[20,24],"recognizing":[21],"exploit":[25],"spatial":[27],"relationships":[28],"between":[29,52],"different":[30],"ingredients":[31],"(such":[32],"as":[33,80],"meat":[34],"and":[35],"bread":[36],"a":[38,42,57,73,81,85],"sandwich).":[39],"propose":[41],"new":[43],"representation":[44,94],"for":[45,84],"calculates":[49],"pairwise":[50],"statistics":[51,71],"local":[53],"features":[54],"computed":[55],"over":[56],"soft":[58],"pixel-level":[59],"segmentation":[60],"of":[61],"image":[63],"into":[64],"eight":[65],"ingredient":[66],"types.":[67],"accumulate":[69],"these":[70],"multi-dimensional":[74],"histogram,":[75],"which":[76],"then":[78],"used":[79],"feature":[82],"vector":[83],"discriminative":[86],"classifier.":[87],"Our":[88],"experiments":[89],"show":[90],"proposed":[93],"significantly":[96],"more":[97],"accurate":[98],"at":[99],"identifying":[100],"than":[102],"existing":[103],"methods.":[104]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":15},{"year":2023,"cited_by_count":18},{"year":2022,"cited_by_count":14},{"year":2021,"cited_by_count":25},{"year":2020,"cited_by_count":20},{"year":2019,"cited_by_count":20},{"year":2018,"cited_by_count":15},{"year":2017,"cited_by_count":22},{"year":2016,"cited_by_count":24},{"year":2015,"cited_by_count":33},{"year":2014,"cited_by_count":24},{"year":2013,"cited_by_count":9},{"year":2012,"cited_by_count":14}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}