{"id":"https://openalex.org/W2154469405","doi":"https://doi.org/10.1109/cvpr.2008.4587379","title":"A joint appearance-spatial distance for kernel-based image categorization","display_name":"A joint appearance-spatial distance for kernel-based image categorization","publication_year":2008,"publication_date":"2008-06-01","ids":{"openalex":"https://openalex.org/W2154469405","doi":"https://doi.org/10.1109/cvpr.2008.4587379","mag":"2154469405"},"language":"en","primary_location":{"id":"doi:10.1109/cvpr.2008.4587379","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2008.4587379","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 IEEE 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/A5100766907","display_name":"Guo-Jun Qi","orcid":"https://orcid.org/0000-0003-3508-1851"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Guo-Jun Qi","raw_affiliation_strings":["MOE-Microsoft Key Laboratory of Multimedia Computing and Communication & Department of Automation, University of Science and Technology, Hefei, Anhui, China"],"affiliations":[{"raw_affiliation_string":"MOE-Microsoft Key Laboratory of Multimedia Computing and Communication & Department of Automation, University of Science and Technology, Hefei, Anhui, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001983464","display_name":"Xian-Sheng Hua","orcid":null},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xian-Sheng Hua","raw_affiliation_strings":["Microsoft Research Asia, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Microsoft Research Asia, Beijing, China","institution_ids":["https://openalex.org/I4210113369"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100728762","display_name":"Yong Rui","orcid":"https://orcid.org/0000-0002-9142-5914"},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yong Rui","raw_affiliation_strings":["Microsoft Research Asia, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Microsoft Research Asia, Beijing, China","institution_ids":["https://openalex.org/I4210113369"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035112538","display_name":"Jinhui Tang","orcid":"https://orcid.org/0000-0001-9008-222X"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinhui Tang","raw_affiliation_strings":["MOE-Microsoft Key Laboratory of Multimedia Computing and Communication & Department of Automation, University of Science and Technology, Hefei, Anhui, China"],"affiliations":[{"raw_affiliation_string":"MOE-Microsoft Key Laboratory of Multimedia Computing and Communication & Department of Automation, University of Science and Technology, Hefei, Anhui, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003217535","display_name":"Zheng-Jun Zha","orcid":"https://orcid.org/0000-0003-2510-8993"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zheng-Jun Zha","raw_affiliation_strings":["MOE-Microsoft Key Laboratory of Multimedia Computing and Communication & Department of Automation, University of Science and Technology, Hefei, Anhui, China"],"affiliations":[{"raw_affiliation_string":"MOE-Microsoft Key Laboratory of Multimedia Computing and Communication & Department of Automation, University of Science and Technology, Hefei, Anhui, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100397026","display_name":"Hao Zhang","orcid":"https://orcid.org/0000-0003-1991-119X"},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hong-Jiang Zhang","raw_affiliation_strings":["Microsoft Research Asia, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Microsoft Research Asia, Beijing, China","institution_ids":["https://openalex.org/I4210113369"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5100766907"],"corresponding_institution_ids":["https://openalex.org/I126520041"],"apc_list":null,"apc_paid":null,"fwci":2.8377,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.91649328,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9991999864578247,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9962999820709229,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6742652058601379},{"id":"https://openalex.org/keywords/categorization","display_name":"Categorization","score":0.6620664596557617},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.661774754524231},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.653052568435669},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6403809189796448},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.5940580368041992},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5886503458023071},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4716581404209137},{"id":"https://openalex.org/keywords/joint","display_name":"Joint (building)","score":0.46528688073158264},{"id":"https://openalex.org/keywords/distance-measures","display_name":"Distance measures","score":0.4643419682979584},{"id":"https://openalex.org/keywords/upper-and-lower-bounds","display_name":"Upper and lower bounds","score":0.4585340917110443},{"id":"https://openalex.org/keywords/spatial-analysis","display_name":"Spatial analysis","score":0.4253080189228058},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.33368703722953796},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.2970978021621704},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.0959082543849945}],"concepts":[{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6742652058601379},{"id":"https://openalex.org/C94124525","wikidata":"https://www.wikidata.org/wiki/Q912550","display_name":"Categorization","level":2,"score":0.6620664596557617},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.661774754524231},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.653052568435669},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6403809189796448},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.5940580368041992},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5886503458023071},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4716581404209137},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.46528688073158264},{"id":"https://openalex.org/C2639959","wikidata":"https://www.wikidata.org/wiki/Q1344778","display_name":"Distance measures","level":2,"score":0.4643419682979584},{"id":"https://openalex.org/C77553402","wikidata":"https://www.wikidata.org/wiki/Q13222579","display_name":"Upper and lower bounds","level":2,"score":0.4585340917110443},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.4253080189228058},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.33368703722953796},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2970978021621704},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0959082543849945},{"id":"https://openalex.org/C170154142","wikidata":"https://www.wikidata.org/wiki/Q150737","display_name":"Architectural engineering","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"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/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","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/cvpr.2008.4587379","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2008.4587379","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 IEEE Conference on Computer Vision and Pattern Recognition","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.603.1234","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.603.1234","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://research.microsoft.com/en-us/um/people/yongrui/ps/2008_cvpr_joint_distance.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6000000238418579,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1537581649","https://openalex.org/W1699734612","https://openalex.org/W2024581784","https://openalex.org/W2098166271","https://openalex.org/W2099111195","https://openalex.org/W2099189408","https://openalex.org/W2100969003","https://openalex.org/W2104978738","https://openalex.org/W2107034620","https://openalex.org/W2125145210","https://openalex.org/W2150120413","https://openalex.org/W2153635508","https://openalex.org/W2154054404","https://openalex.org/W2154422044","https://openalex.org/W2159727956","https://openalex.org/W2162915993","https://openalex.org/W2165828254","https://openalex.org/W2478708596","https://openalex.org/W6674851815","https://openalex.org/W6678315040","https://openalex.org/W6684893555"],"related_works":["https://openalex.org/W2165912799","https://openalex.org/W2735662278","https://openalex.org/W2382615723","https://openalex.org/W4311804456","https://openalex.org/W1987484445","https://openalex.org/W2623658258","https://openalex.org/W2143413548","https://openalex.org/W1969219540","https://openalex.org/W2370459448","https://openalex.org/W2105067402"],"abstract_inverted_index":{"The":[0,24],"goal":[1],"of":[2,10,16,83],"image":[3,22,71,100],"categorization":[4],"is":[5,77],"to":[6,19,99],"classify":[7],"a":[8,14,41,45,63,74,93,116],"collection":[9],"unlabeled":[11],"images":[12],"into":[13],"set":[15],"predefined":[17],"classes":[18],"support":[20],"semantic-level":[21],"retrieval.":[23],"distance":[25,48,65,75],"measures":[26,49],"used":[27,38],"in":[28,40,58,92],"most":[29],"existing":[30],"approaches":[31],"either":[32],"ignored":[33],"the":[34,104,129,134],"spatial":[35],"structures":[36],"or":[37],"them":[39],"separate":[42],"step.":[43],"As":[44],"result,":[46],"these":[47,56],"achieved":[50],"only":[51],"limited":[52],"success.":[53],"To":[54],"address":[55],"difficulties,":[57],"this":[59],"paper,":[60],"we":[61],"propose":[62],"new":[64],"measure":[66,76],"that":[67,96,128],"integrates":[68],"joint":[69],"appearance-spatial":[70],"features.":[72],"Such":[73],"computed":[78,90],"as":[79],"an":[80,84],"upper":[81,105],"bound":[82,106],"information-theoretic":[85],"discrimination,":[86],"and":[87],"can":[88,108],"be":[89,109],"efficiently":[91],"recursive":[94],"formulation":[95],"scales":[97],"well":[98],"size.":[101],"In":[102],"addition,":[103],"approximation":[107],"further":[110],"tightened":[111],"via":[112],"adaption":[113],"learning":[114],"from":[115],"universal":[117],"reference":[118],"model.":[119],"Extensive":[120],"experiments":[121],"on":[122],"two":[123],"widely-used":[124],"data":[125],"sets":[126],"show":[127],"proposed":[130],"approach":[131],"significantly":[132],"outperforms":[133],"state-of-the-art":[135],"approaches.":[136]},"counts_by_year":[{"year":2012,"cited_by_count":2}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}
