{"id":"https://openalex.org/W2078077974","doi":"https://doi.org/10.1145/2811411.2811486","title":"Fast stereo-based pedestrian detection using hypotheses","display_name":"Fast stereo-based pedestrian detection using hypotheses","publication_year":2015,"publication_date":"2015-10-09","ids":{"openalex":"https://openalex.org/W2078077974","doi":"https://doi.org/10.1145/2811411.2811486","mag":"2078077974"},"language":"en","primary_location":{"id":"doi:10.1145/2811411.2811486","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2811411.2811486","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2015 Conference on research in adaptive and convergent systems","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/A5103203864","display_name":"Min-Sung Kang","orcid":"https://orcid.org/0000-0002-8459-5843"},"institutions":[{"id":"https://openalex.org/I193352282","display_name":"Daegu Gyeongbuk Institute of Science and Technology","ror":"https://ror.org/03frjya69","country_code":"KR","type":"education","lineage":["https://openalex.org/I193352282"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Min-Sung Kang","raw_affiliation_strings":["DGIST, Hyeonpung-Myeon, Dalseong-Gun Daegu, South KOREA"],"affiliations":[{"raw_affiliation_string":"DGIST, Hyeonpung-Myeon, Dalseong-Gun Daegu, South KOREA","institution_ids":["https://openalex.org/I193352282"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5114255846","display_name":"Young-Chul Lim","orcid":null},"institutions":[{"id":"https://openalex.org/I193352282","display_name":"Daegu Gyeongbuk Institute of Science and Technology","ror":"https://ror.org/03frjya69","country_code":"KR","type":"education","lineage":["https://openalex.org/I193352282"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Young-Chul Lim","raw_affiliation_strings":["DGIST, Hyeonpung-Myeon, Dalseong-Gun Daegu, South KOREA"],"affiliations":[{"raw_affiliation_string":"DGIST, Hyeonpung-Myeon, Dalseong-Gun Daegu, South KOREA","institution_ids":["https://openalex.org/I193352282"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5103203864"],"corresponding_institution_ids":["https://openalex.org/I193352282"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.0763961,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"131","last_page":"135"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9998000264167786,"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":0.9998000264167786,"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/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9979000091552734,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive 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/T10036","display_name":"Advanced Neural Network Applications","score":0.9927999973297119,"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/obstacle","display_name":"Obstacle","score":0.8695253133773804},{"id":"https://openalex.org/keywords/pedestrian-detection","display_name":"Pedestrian detection","score":0.8461745977401733},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.749309778213501},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.707850992679596},{"id":"https://openalex.org/keywords/pedestrian","display_name":"Pedestrian","score":0.7008860111236572},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.5821213126182556},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.550687849521637},{"id":"https://openalex.org/keywords/component","display_name":"Component (thermodynamics)","score":0.5057904720306396},{"id":"https://openalex.org/keywords/data-association","display_name":"Data association","score":0.4833521544933319},{"id":"https://openalex.org/keywords/association","display_name":"Association (psychology)","score":0.482625812292099},{"id":"https://openalex.org/keywords/stereopsis","display_name":"Stereopsis","score":0.46254464983940125},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.45221439003944397},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.4469109773635864},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.20100894570350647},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.10026240348815918},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.08340173959732056}],"concepts":[{"id":"https://openalex.org/C2776650193","wikidata":"https://www.wikidata.org/wiki/Q264661","display_name":"Obstacle","level":2,"score":0.8695253133773804},{"id":"https://openalex.org/C2780156472","wikidata":"https://www.wikidata.org/wiki/Q2355550","display_name":"Pedestrian detection","level":3,"score":0.8461745977401733},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.749309778213501},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.707850992679596},{"id":"https://openalex.org/C2777113093","wikidata":"https://www.wikidata.org/wiki/Q221488","display_name":"Pedestrian","level":2,"score":0.7008860111236572},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.5821213126182556},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.550687849521637},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.5057904720306396},{"id":"https://openalex.org/C2983325608","wikidata":"https://www.wikidata.org/wiki/Q17084606","display_name":"Data association","level":3,"score":0.4833521544933319},{"id":"https://openalex.org/C142853389","wikidata":"https://www.wikidata.org/wiki/Q744778","display_name":"Association (psychology)","level":2,"score":0.482625812292099},{"id":"https://openalex.org/C68537008","wikidata":"https://www.wikidata.org/wiki/Q247932","display_name":"Stereopsis","level":2,"score":0.46254464983940125},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.45221439003944397},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.4469109773635864},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.20100894570350647},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.10026240348815918},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.08340173959732056},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"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/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2811411.2811486","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2811411.2811486","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2015 Conference on research in adaptive and convergent systems","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11","score":0.5799999833106995}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W161578567","https://openalex.org/W1558922706","https://openalex.org/W1924453835","https://openalex.org/W2025991977","https://openalex.org/W2031454541","https://openalex.org/W2098792943","https://openalex.org/W2099355420","https://openalex.org/W2102157586","https://openalex.org/W2104572919","https://openalex.org/W2118810648","https://openalex.org/W2121955477","https://openalex.org/W2136767008","https://openalex.org/W2145951052","https://openalex.org/W2159107954","https://openalex.org/W2159954538","https://openalex.org/W2161969291","https://openalex.org/W2163943109","https://openalex.org/W2165114467","https://openalex.org/W2167049458","https://openalex.org/W4244952642"],"related_works":["https://openalex.org/W2972620127","https://openalex.org/W2981141433","https://openalex.org/W2802018156","https://openalex.org/W2101531944","https://openalex.org/W4313315626","https://openalex.org/W2922437833","https://openalex.org/W4312696271","https://openalex.org/W4223892596","https://openalex.org/W2933098581","https://openalex.org/W2556125083"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3],"present":[4],"a":[5],"multiple":[6,16,51,58],"hypotheses":[7,17,56],"framework":[8,18],"to":[9,53],"detect":[10],"pedestrians":[11],"accurately":[12],"and":[13,25,72],"precisely.":[14],"The":[15,46,61],"consists":[19],"of":[20,74,77],"obstacle":[21],"detection,":[22],"pedestrian":[23],"recognition":[24,37],"data":[26,47],"association.":[27],"Obstacle":[28],"detection":[29],"detects":[30],"all":[31],"obstacles":[32,41],"on":[33],"the":[34,39,54,66,70,75],"road.":[35],"Pedestrian":[36],"classifies":[38],"detected":[40],"as":[42],"persons":[43],"or":[44],"non-persons.":[45],"association":[48],"component":[49],"assigns":[50],"results":[52,63],"correct":[55],"with":[57],"similarity":[59],"functions.":[60],"experimental":[62],"demonstrate":[64],"that":[65],"proposed":[67],"method":[68],"enhances":[69],"accuracy":[71],"precision":[73],"region":[76],"interest.":[78]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}