{"id":"https://openalex.org/W2609777586","doi":"https://doi.org/10.1109/icpr.2016.7900197","title":"Unsupervised object counting without object recognition","display_name":"Unsupervised object counting without object recognition","publication_year":2016,"publication_date":"2016-12-01","ids":{"openalex":"https://openalex.org/W2609777586","doi":"https://doi.org/10.1109/icpr.2016.7900197","mag":"2609777586"},"language":"en","primary_location":{"id":"doi:10.1109/icpr.2016.7900197","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2016.7900197","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 23rd International Conference on Pattern Recognition (ICPR)","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/A5086948083","display_name":"Takayuki Katsuki","orcid":"https://orcid.org/0000-0002-3670-1138"},"institutions":[{"id":"https://openalex.org/I4210145865","display_name":"IBM Research - Tokyo","ror":"https://ror.org/04915qk43","country_code":"JP","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210114115","https://openalex.org/I4210145865"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Takayuki Katsuki","raw_affiliation_strings":["IBM Research-Tokyo, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"IBM Research-Tokyo, Tokyo, Japan","institution_ids":["https://openalex.org/I4210145865"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089173802","display_name":"Tetsuro Morimura","orcid":"https://orcid.org/0009-0002-9711-8023"},"institutions":[{"id":"https://openalex.org/I4210145865","display_name":"IBM Research - Tokyo","ror":"https://ror.org/04915qk43","country_code":"JP","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210114115","https://openalex.org/I4210145865"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Tetsuro Morimura","raw_affiliation_strings":["IBM Research-Tokyo, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"IBM Research-Tokyo, Tokyo, Japan","institution_ids":["https://openalex.org/I4210145865"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5022048163","display_name":"Tsuyoshi Id\u00e9","orcid":"https://orcid.org/0000-0001-8993-2776"},"institutions":[{"id":"https://openalex.org/I4210114115","display_name":"IBM Research - Thomas J. Watson Research Center","ror":"https://ror.org/0265w5591","country_code":"US","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210114115"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tsuyoshi Ide","raw_affiliation_strings":["IBM T. J. Watson Research Center, New York"],"affiliations":[{"raw_affiliation_string":"IBM T. J. Watson Research Center, New York","institution_ids":["https://openalex.org/I4210114115"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5086948083"],"corresponding_institution_ids":["https://openalex.org/I4210145865"],"apc_list":null,"apc_paid":null,"fwci":0.501,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.75039858,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"9","issue":null,"first_page":"3627","last_page":"3632"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9995999932289124,"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":0.9995999932289124,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.991599977016449,"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"}},{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9797000288963318,"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/robustness","display_name":"Robustness (evolution)","score":0.732006847858429},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.7119535207748413},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7073190212249756},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6931629180908203},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.562929630279541},{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.5608474612236023},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.553941011428833},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5352457761764526},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.5281731486320496},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5106714367866516},{"id":"https://openalex.org/keywords/constraint","display_name":"Constraint (computer-aided design)","score":0.49749234318733215},{"id":"https://openalex.org/keywords/cognitive-neuroscience-of-visual-object-recognition","display_name":"Cognitive neuroscience of visual object recognition","score":0.4740837812423706},{"id":"https://openalex.org/keywords/counting-process","display_name":"Counting process","score":0.45845121145248413},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.39434105157852173},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.322898268699646},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.20029067993164062},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.08246791362762451}],"concepts":[{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.732006847858429},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.7119535207748413},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7073190212249756},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6931629180908203},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.562929630279541},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.5608474612236023},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.553941011428833},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5352457761764526},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.5281731486320496},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5106714367866516},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.49749234318733215},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.4740837812423706},{"id":"https://openalex.org/C2781104640","wikidata":"https://www.wikidata.org/wiki/Q11827313","display_name":"Counting process","level":2,"score":0.45845121145248413},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.39434105157852173},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.322898268699646},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.20029067993164062},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.08246791362762451},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icpr.2016.7900197","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2016.7900197","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 23rd International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320338075","display_name":"Core Research for Evolutional Science and Technology","ror":"https://ror.org/00097mb19"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":56,"referenced_works":["https://openalex.org/W29756976","https://openalex.org/W614214702","https://openalex.org/W1165849685","https://openalex.org/W1542079534","https://openalex.org/W1585123347","https://openalex.org/W1608462934","https://openalex.org/W1618600317","https://openalex.org/W1630491267","https://openalex.org/W1633866186","https://openalex.org/W1833498382","https://openalex.org/W1884372994","https://openalex.org/W1989702938","https://openalex.org/W2031489346","https://openalex.org/W2035710656","https://openalex.org/W2036549113","https://openalex.org/W2049004244","https://openalex.org/W2086019232","https://openalex.org/W2088929512","https://openalex.org/W2098062695","https://openalex.org/W2107777165","https://openalex.org/W2127498532","https://openalex.org/W2132713448","https://openalex.org/W2134650809","https://openalex.org/W2135874888","https://openalex.org/W2136767008","https://openalex.org/W2137479423","https://openalex.org/W2139479830","https://openalex.org/W2140124448","https://openalex.org/W2144250161","https://openalex.org/W2145983039","https://openalex.org/W2151967501","https://openalex.org/W2161841955","https://openalex.org/W2164598857","https://openalex.org/W2182277027","https://openalex.org/W2192902519","https://openalex.org/W2198400865","https://openalex.org/W2204461283","https://openalex.org/W2396600439","https://openalex.org/W2397915214","https://openalex.org/W2963314466","https://openalex.org/W3151739637","https://openalex.org/W4300554907","https://openalex.org/W6632569617","https://openalex.org/W6634962694","https://openalex.org/W6636504819","https://openalex.org/W6636506271","https://openalex.org/W6636674445","https://openalex.org/W6636924774","https://openalex.org/W6638813818","https://openalex.org/W6639557182","https://openalex.org/W6681320109","https://openalex.org/W6681368121","https://openalex.org/W6682569104","https://openalex.org/W6685892137","https://openalex.org/W6688112068","https://openalex.org/W6712536872"],"related_works":["https://openalex.org/W1975321310","https://openalex.org/W1952261593","https://openalex.org/W2014494654","https://openalex.org/W2990323019","https://openalex.org/W3130349901","https://openalex.org/W1579833936","https://openalex.org/W2107361128","https://openalex.org/W2095350775","https://openalex.org/W1992295166","https://openalex.org/W2143508933"],"abstract_inverted_index":{"This":[0],"paper":[1],"addresses":[2],"the":[3,12,24,31,42,50,82,94,98,105,118,123],"problem":[4,25,106],"of":[5,14,16,30,38,107,122,135],"object":[6,62],"counting,":[7],"which":[8,58],"is":[9,79],"to":[10,49,80,88,92,104,133],"estimate":[11],"number":[13],"objects":[15],"interest":[17],"from":[18],"an":[19],"input":[20,43],"observation.":[21],"We":[22,100],"formalize":[23],"as":[26,85,97],"a":[27,35,86],"posterior":[28],"inference":[29],"count":[32],"by":[33],"introducing":[34],"particular":[36],"type":[37],"Gaussian":[39],"mixture":[40,46,95],"for":[41],"observation,":[44],"whose":[45],"indexes":[47,96],"correspond":[48],"count.":[51,99],"Unlike":[52],"existing":[53],"approaches":[54],"in":[55,110],"image":[56],"analysis,":[57],"typically":[59],"perform":[60],"explicit":[61],"detection":[63],"using":[64],"labeled":[65,74,128],"training":[66,75,129],"images,":[67],"our":[68,102],"approach":[69,125],"does":[70],"not":[71],"need":[72],"any":[73,127],"data.":[76],"Our":[77],"idea":[78],"use":[81],"stick-breaking":[83],"process":[84],"constraint":[87],"make":[89],"it":[90],"possible":[91],"interpret":[93],"apply":[101],"method":[103],"counting":[108],"vehicles":[109],"real-world":[111],"web":[112],"camera":[113],"images":[114],"and":[115,120],"demonstrate":[116],"that":[117],"accuracy":[119],"robustness":[121],"proposed":[124],"without":[126],"data":[130],"are":[131],"comparable":[132],"those":[134],"supervised":[136],"alternatives.":[137]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2019,"cited_by_count":1},{"year":2016,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
