{"id":"https://openalex.org/W2007027649","doi":"https://doi.org/10.1109/tvcg.2014.2346446","title":"City Forensics: Using Visual Elements to Predict Non-Visual City Attributes","display_name":"City Forensics: Using Visual Elements to Predict Non-Visual City Attributes","publication_year":2014,"publication_date":"2014-08-11","ids":{"openalex":"https://openalex.org/W2007027649","doi":"https://doi.org/10.1109/tvcg.2014.2346446","mag":"2007027649","pmid":"https://pubmed.ncbi.nlm.nih.gov/26356976"},"language":"en","primary_location":{"id":"doi:10.1109/tvcg.2014.2346446","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tvcg.2014.2346446","pdf_url":null,"source":{"id":"https://openalex.org/S84775595","display_name":"IEEE Transactions on Visualization and Computer Graphics","issn_l":"1077-2626","issn":["1077-2626","1941-0506","2160-9306"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["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 Visualization and Computer Graphics","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/A5004676508","display_name":"Sean M. Arietta","orcid":null},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Sean M. Arietta","raw_affiliation_strings":["EECS Department, University of California, Berkeley","EECS Dept., Univ. of California, Berkeley"],"affiliations":[{"raw_affiliation_string":"EECS Department, University of California, Berkeley","institution_ids":["https://openalex.org/I95457486"]},{"raw_affiliation_string":"EECS Dept., Univ. of California, Berkeley","institution_ids":["https://openalex.org/I95457486"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077436220","display_name":"Alexei A. Efros","orcid":"https://orcid.org/0000-0001-5720-8070"},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Alexei A. Efros","raw_affiliation_strings":["EECS Department, University of California, Berkeley","EECS Dept., Univ. of California, Berkeley"],"affiliations":[{"raw_affiliation_string":"EECS Department, University of California, Berkeley","institution_ids":["https://openalex.org/I95457486"]},{"raw_affiliation_string":"EECS Dept., Univ. of California, Berkeley","institution_ids":["https://openalex.org/I95457486"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034754633","display_name":"Ravi Ramamoorthi","orcid":"https://orcid.org/0000-0003-3993-5789"},"institutions":[{"id":"https://openalex.org/I36258959","display_name":"University of California, San Diego","ror":"https://ror.org/0168r3w48","country_code":"US","type":"education","lineage":["https://openalex.org/I36258959"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ravi Ramamoorthi","raw_affiliation_strings":["CSE Department, University of California, San Diego","CSE Dept., University of California San Diego#TAB#"],"affiliations":[{"raw_affiliation_string":"CSE Department, University of California, San Diego","institution_ids":["https://openalex.org/I36258959"]},{"raw_affiliation_string":"CSE Dept., University of California San Diego#TAB#","institution_ids":["https://openalex.org/I36258959"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5045835385","display_name":"Maneesh Agrawala","orcid":"https://orcid.org/0000-0002-8996-7327"},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Maneesh Agrawala","raw_affiliation_strings":["EECS Department, University of California, Berkeley","EECS Dept., Univ. of California, Berkeley"],"affiliations":[{"raw_affiliation_string":"EECS Department, University of California, Berkeley","institution_ids":["https://openalex.org/I95457486"]},{"raw_affiliation_string":"EECS Dept., Univ. of California, Berkeley","institution_ids":["https://openalex.org/I95457486"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5004676508"],"corresponding_institution_ids":["https://openalex.org/I95457486"],"apc_list":null,"apc_paid":null,"fwci":8.8968,"has_fulltext":false,"cited_by_count":146,"citation_normalized_percentile":{"value":0.98359896,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":"20","issue":"12","first_page":"2624","last_page":"2633"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9965000152587891,"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":0.9965000152587891,"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/T10574","display_name":"Crime Patterns and Interventions","score":0.9850000143051147,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9815000295639038,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/computer-science","display_name":"Computer science","score":0.7778515815734863},{"id":"https://openalex.org/keywords/bottleneck","display_name":"Bottleneck","score":0.6364378333091736},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6152713894844055},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.5633512139320374},{"id":"https://openalex.org/keywords/population","display_name":"Population","score":0.5454587936401367},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.477285772562027},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.46465864777565},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.4474383592605591},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.446189284324646},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.44098618626594543},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3618836998939514},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.0937676727771759}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7778515815734863},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.6364378333091736},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6152713894844055},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.5633512139320374},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.5454587936401367},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.477285772562027},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.46465864777565},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.4474383592605591},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.446189284324646},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.44098618626594543},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3618836998939514},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0937676727771759},{"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/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.0},{"id":"https://openalex.org/C149923435","wikidata":"https://www.wikidata.org/wiki/Q37732","display_name":"Demography","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/tvcg.2014.2346446","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tvcg.2014.2346446","pdf_url":null,"source":{"id":"https://openalex.org/S84775595","display_name":"IEEE Transactions on Visualization and Computer Graphics","issn_l":"1077-2626","issn":["1077-2626","1941-0506","2160-9306"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["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 Visualization and Computer Graphics","raw_type":"journal-article"},{"id":"pmid:26356976","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/26356976","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 visualization and computer graphics","raw_type":null},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.467.5590","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.467.5590","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://vis.berkeley.edu/papers/cityforensics/paper.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.6100000143051147}],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320332195","display_name":"Samsung","ror":"https://ror.org/04w3jy968"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":50,"referenced_works":["https://openalex.org/W265421414","https://openalex.org/W564943520","https://openalex.org/W1487583988","https://openalex.org/W1487615702","https://openalex.org/W1521365818","https://openalex.org/W1525292367","https://openalex.org/W1553311539","https://openalex.org/W1572666543","https://openalex.org/W1590510366","https://openalex.org/W1964357740","https://openalex.org/W1964856687","https://openalex.org/W1968147892","https://openalex.org/W1979728958","https://openalex.org/W2001249877","https://openalex.org/W2035430745","https://openalex.org/W2039402388","https://openalex.org/W2055132753","https://openalex.org/W2068883041","https://openalex.org/W2072595688","https://openalex.org/W2080378521","https://openalex.org/W2081612620","https://openalex.org/W2086312876","https://openalex.org/W2086908079","https://openalex.org/W2087347434","https://openalex.org/W2101468243","https://openalex.org/W2102605133","https://openalex.org/W2107156034","https://openalex.org/W2114122776","https://openalex.org/W2114892120","https://openalex.org/W2117088012","https://openalex.org/W2118572719","https://openalex.org/W2120419212","https://openalex.org/W2123503110","https://openalex.org/W2132455584","https://openalex.org/W2137046698","https://openalex.org/W2146814781","https://openalex.org/W2153635508","https://openalex.org/W2156484217","https://openalex.org/W2157825442","https://openalex.org/W2161969291","https://openalex.org/W2163605009","https://openalex.org/W2166445532","https://openalex.org/W2169528473","https://openalex.org/W2171322814","https://openalex.org/W2963542991","https://openalex.org/W4238070559","https://openalex.org/W4248151413","https://openalex.org/W6629368666","https://openalex.org/W6635258101","https://openalex.org/W6684191040"],"related_works":["https://openalex.org/W2595172197","https://openalex.org/W2084856301","https://openalex.org/W2127970246","https://openalex.org/W4382618745","https://openalex.org/W2885125400","https://openalex.org/W1001352512","https://openalex.org/W1989889224","https://openalex.org/W2748922771","https://openalex.org/W2011430815","https://openalex.org/W4321606653"],"abstract_inverted_index":{"We":[0,56,118,155],"present":[1,183],"a":[2,16,31,59,63,82,108,124,131],"method":[3],"for":[4,160,219],"automatically":[5],"identifying":[6],"and":[7,18,36,130,150,167,213],"validating":[8],"predictive":[9,125],"relationships":[10],"between":[11,127],"the":[12,48,54,90,151,194],"visual":[13,45,95,128,195,217],"appearance":[14],"of":[15,33,40,53,65,100,110,133,153,197],"city":[17,111,134,198,211],"its":[19],"non-visual":[20],"attributes":[21,112,135],"(e.g.":[22],"crime":[23,138],"statistics,":[24],"housing":[25,142],"prices,":[26,143],"population":[27,144],"density":[28],"etc.).":[29],"Given":[30],"set":[32,64],"street-level":[34,165],"images":[35,49,166],"(location,":[37],"city-attribute-value)":[38],"pairs":[39],"measurements,":[41],"we":[42,80,182],"first":[43],"identify":[44],"elements":[46,69,129,218],"in":[47],"that":[50,87,120,169,187,204],"are":[51],"discriminative":[52],"attribute.":[55],"then":[57],"train":[58],"predictor":[60,171],"by":[61,97],"learning":[62],"weights":[66],"over":[67],"these":[68,77],"using":[70],"non-linear":[71],"Support":[72],"Vector":[73],"Regression.":[74],"To":[75],"perform":[76],"operations":[78],"efficiently,":[79],"implement":[81],"scalable":[83],"distributed":[84],"processing":[85],"framework":[86],"speeds":[88],"up":[89],"main":[91],"computational":[92],"bottleneck":[93],"(extracting":[94],"elements)":[96],"an":[98],"order":[99],"magnitude.":[101],"This":[102],"speedup":[103],"allows":[104],"us":[105],"to":[106,191,210],"investigate":[107],"variety":[109],"across":[113],"6":[114],"different":[115],"American":[116],"cities.":[117],"find":[119],"indeed":[121],"there":[122],"is":[123],"relationship":[126],"number":[132],"including":[136],"violent":[137],"rates,":[139,141],"theft":[140,162],"density,":[145],"tree":[146],"presence,":[147,149],"graffiti":[148],"perception":[152],"danger.":[154],"also":[156],"test":[157],"human":[158],"performance":[159],"predicting":[161],"based":[163],"on":[164,179],"show":[168],"our":[170,189],"outperforms":[172],"this":[173],"baseline":[174],"with":[175],"33%":[176],"higher":[177],"accuracy":[178],"average.":[180],"Finally,":[181],"three":[184],"prototype":[185],"applications":[186],"use":[188],"system":[190],"(1)":[192],"define":[193],"boundary":[196],"neighborhoods,":[199],"(2)":[200],"generate":[201],"walking":[202],"directions":[203],"avoid":[205],"or":[206],"seek":[207],"out":[208],"exposure":[209],"attributes,":[212],"(3)":[214],"validate":[215],"user-specified":[216],"prediction.":[220]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":16},{"year":2021,"cited_by_count":19},{"year":2020,"cited_by_count":16},{"year":2019,"cited_by_count":17},{"year":2018,"cited_by_count":16},{"year":2017,"cited_by_count":20},{"year":2016,"cited_by_count":10},{"year":2015,"cited_by_count":5},{"year":2014,"cited_by_count":1}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}
