{"id":"https://openalex.org/W2028334899","doi":"https://doi.org/10.1109/icip.2012.6467125","title":"Markov random field-based real-time detection of intentionally-captured persons","display_name":"Markov random field-based real-time detection of intentionally-captured persons","publication_year":2012,"publication_date":"2012-09-01","ids":{"openalex":"https://openalex.org/W2028334899","doi":"https://doi.org/10.1109/icip.2012.6467125","mag":"2028334899"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2012.6467125","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2012.6467125","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 19th IEEE International Conference on Image Processing","raw_type":"proceedings-article"},"type":"conference-paper","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/A5112700499","display_name":"Tatsuya KOYAMA","orcid":null},"institutions":[{"id":"https://openalex.org/I98285908","display_name":"The University of Osaka","ror":"https://ror.org/035t8zc32","country_code":"JP","type":"education","lineage":["https://openalex.org/I98285908"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Tatsuya Koyama","raw_affiliation_strings":["School of Engineering, Osaka University, Suita, Osaka, Japan","School of Engineering, Osaka University, Suita, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Engineering, Osaka University, Suita, Osaka, Japan","institution_ids":["https://openalex.org/I98285908"]},{"raw_affiliation_string":"School of Engineering, Osaka University, Suita, Japan","institution_ids":["https://openalex.org/I98285908"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065649079","display_name":"Yuta Nakashima","orcid":"https://orcid.org/0000-0001-8000-3567"},"institutions":[{"id":"https://openalex.org/I98285908","display_name":"The University of Osaka","ror":"https://ror.org/035t8zc32","country_code":"JP","type":"education","lineage":["https://openalex.org/I98285908"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yuta Nakashima","raw_affiliation_strings":["Graduate School of Engineering, Osaka University, Suita, Osaka, Japan","Grad. Sch. of Eng., Osaka Univ., Suita, Japan#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of Engineering, Osaka University, Suita, Osaka, Japan","institution_ids":["https://openalex.org/I98285908"]},{"raw_affiliation_string":"Grad. Sch. of Eng., Osaka Univ., Suita, Japan#TAB#","institution_ids":["https://openalex.org/I98285908"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5068454170","display_name":"Noboru Babaguchi","orcid":"https://orcid.org/0000-0003-3320-896X"},"institutions":[{"id":"https://openalex.org/I98285908","display_name":"The University of Osaka","ror":"https://ror.org/035t8zc32","country_code":"JP","type":"education","lineage":["https://openalex.org/I98285908"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Noboru Babaguchi","raw_affiliation_strings":["Graduate School of Engineering, Osaka University, Suita, Osaka, Japan","Grad. Sch. of Eng., Osaka Univ., Suita, Japan#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of Engineering, Osaka University, Suita, Osaka, Japan","institution_ids":["https://openalex.org/I98285908"]},{"raw_affiliation_string":"Grad. Sch. of Eng., Osaka Univ., Suita, Japan#TAB#","institution_ids":["https://openalex.org/I98285908"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I98285908"],"apc_list":null,"apc_paid":null,"fwci":0.4512,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.59453173,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"3656","issue":null,"first_page":"1377","last_page":"1380"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9998999834060669,"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/T10331","display_name":"Video Surveillance and Tracking Methods","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/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9994999766349792,"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/T12357","display_name":"Digital Media Forensic Detection","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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7299181222915649},{"id":"https://openalex.org/keywords/markov-random-field","display_name":"Markov random field","score":0.7192111015319824},{"id":"https://openalex.org/keywords/acceleration","display_name":"Acceleration","score":0.687556266784668},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6745152473449707},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6696471571922302},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.593007504940033},{"id":"https://openalex.org/keywords/hidden-markov-model","display_name":"Hidden Markov model","score":0.5564233660697937},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.5022735595703125},{"id":"https://openalex.org/keywords/pairwise-comparison","display_name":"Pairwise comparison","score":0.4918534755706787},{"id":"https://openalex.org/keywords/inertial-measurement-unit","display_name":"Inertial measurement unit","score":0.49051302671432495},{"id":"https://openalex.org/keywords/markov-process","display_name":"Markov process","score":0.4890912175178528},{"id":"https://openalex.org/keywords/motion-estimation","display_name":"Motion estimation","score":0.4781554639339447},{"id":"https://openalex.org/keywords/motion-detection","display_name":"Motion detection","score":0.43537139892578125},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.15588492155075073},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.14559614658355713},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1375536322593689},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1019875705242157}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7299181222915649},{"id":"https://openalex.org/C2778045648","wikidata":"https://www.wikidata.org/wiki/Q176827","display_name":"Markov random field","level":4,"score":0.7192111015319824},{"id":"https://openalex.org/C117896860","wikidata":"https://www.wikidata.org/wiki/Q11376","display_name":"Acceleration","level":2,"score":0.687556266784668},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6745152473449707},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6696471571922302},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.593007504940033},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.5564233660697937},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.5022735595703125},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.4918534755706787},{"id":"https://openalex.org/C79061980","wikidata":"https://www.wikidata.org/wiki/Q941680","display_name":"Inertial measurement unit","level":2,"score":0.49051302671432495},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.4890912175178528},{"id":"https://openalex.org/C10161872","wikidata":"https://www.wikidata.org/wiki/Q557891","display_name":"Motion estimation","level":2,"score":0.4781554639339447},{"id":"https://openalex.org/C2780624872","wikidata":"https://www.wikidata.org/wiki/Q852453","display_name":"Motion detection","level":3,"score":0.43537139892578125},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.15588492155075073},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.14559614658355713},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1375536322593689},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1019875705242157},{"id":"https://openalex.org/C74650414","wikidata":"https://www.wikidata.org/wiki/Q11397","display_name":"Classical 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},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip.2012.6467125","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2012.6467125","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 19th IEEE International Conference on Image Processing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.5600000023841858,"id":"https://metadata.un.org/sdg/16"}],"awards":[{"id":"https://openalex.org/G3453436115","display_name":"Creation of profit harmonized with disclosure of privacy information","funder_award_id":"24240031","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"}],"funders":[{"id":"https://openalex.org/F4320334764","display_name":"Japan Society for the Promotion of Science","ror":"https://ror.org/00hhkn466"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W1502024436","https://openalex.org/W1964721292","https://openalex.org/W1995446844","https://openalex.org/W2006180404","https://openalex.org/W2130184867","https://openalex.org/W2133206272","https://openalex.org/W2147922961","https://openalex.org/W2151632536","https://openalex.org/W2161969291","https://openalex.org/W2164598857","https://openalex.org/W3148981562","https://openalex.org/W4251874587"],"related_works":["https://openalex.org/W2364370872","https://openalex.org/W2053269318","https://openalex.org/W2091018038","https://openalex.org/W2025614924","https://openalex.org/W2294335174","https://openalex.org/W2225378543","https://openalex.org/W2097963413","https://openalex.org/W4287122200","https://openalex.org/W1591475660","https://openalex.org/W2036630122"],"abstract_inverted_index":{"Most":[0],"videos":[1],"taken":[2],"by":[3],"videographers":[4,15],"contain":[5],"intentionally-captured":[6],"persons":[7],"(ICPs),":[8],"who":[9],"are":[10,56],"essential":[11],"for":[12,59],"what":[13],"the":[14,49,101,106,115],"want":[16],"to":[17,27],"express":[18],"in":[19,30,35,45,125],"their":[20],"video.":[21],"This":[22],"paper":[23],"presents":[24],"a":[25,33,36],"method":[26,119],"detect":[28],"ICPs":[29,107],"real-time.":[31,126],"Whether":[32],"person":[34],"video":[37],"is":[38,43,66],"an":[39],"ICP":[40],"or":[41],"not":[42],"reflected":[44],"features":[46],"such":[47],"as":[48],"person's":[50],"motion":[51,65],"and":[52,77,120],"camera":[53,64,87],"motion,":[54],"which":[55],"thus":[57],"beneficial":[58],"detecting":[60],"ICPs.":[61],"However,":[62],"estimating":[63,86],"computationally":[67],"expensive.":[68],"For":[69],"real-time":[70],"detection,":[71],"we":[72,104],"use":[73],"samples":[74],"of":[75,85,117],"acceleration":[76],"angular":[78],"velocity":[79],"obtained":[80],"from":[81],"inertial":[82],"sensors":[83],"instead":[84],"motion.":[88],"Considering":[89],"that":[90,122],"pairwise":[91],"constraints":[92],"based":[93],"on":[94],"differences":[95],"between":[96],"persons'":[97],"sizes":[98],"also":[99],"improve":[100],"detection":[102],"performance,":[103],"model":[105],"using":[108],"Markov":[109],"random":[110],"field.":[111],"We":[112],"experimentally":[113],"evaluate":[114],"performance":[116],"our":[118],"demonstrate":[121],"it":[123],"works":[124]},"counts_by_year":[{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":1},{"year":2013,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}