{"id":"https://openalex.org/W2889866244","doi":"https://doi.org/10.1109/icip.2018.8451144","title":"Pedestrian Detection in Aerial Images Using Vanishing Point Transformation and Deep Learning","display_name":"Pedestrian Detection in Aerial Images Using Vanishing Point Transformation and Deep Learning","publication_year":2018,"publication_date":"2018-09-07","ids":{"openalex":"https://openalex.org/W2889866244","doi":"https://doi.org/10.1109/icip.2018.8451144","mag":"2889866244"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2018.8451144","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2018.8451144","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 25th IEEE International Conference on Image Processing (ICIP)","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/A5051170606","display_name":"Ya-Ching Chang","orcid":null},"institutions":[{"id":"https://openalex.org/I148366613","display_name":"National Yang Ming Chiao Tung University","ror":"https://ror.org/00se2k293","country_code":"TW","type":"education","lineage":["https://openalex.org/I148366613"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Ya-Ching Chang","raw_affiliation_strings":["Department of Computer Science, National Chiao Tung University, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, National Chiao Tung University, Taiwan","institution_ids":["https://openalex.org/I148366613"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065919129","display_name":"Hua-Tsung Chen","orcid":"https://orcid.org/0000-0002-8084-497X"},"institutions":[{"id":"https://openalex.org/I4880106","display_name":"Feng Chia University","ror":"https://ror.org/05vhczg54","country_code":"TW","type":"education","lineage":["https://openalex.org/I4880106"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Hua-Tsung Chen","raw_affiliation_strings":["Department of Information Engineering and Computer Science, Feng Chia University, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Information Engineering and Computer Science, Feng Chia University, Taiwan","institution_ids":["https://openalex.org/I4880106"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069670059","display_name":"Jen\u2010Hui Chuang","orcid":"https://orcid.org/0000-0002-4934-4811"},"institutions":[{"id":"https://openalex.org/I148366613","display_name":"National Yang Ming Chiao Tung University","ror":"https://ror.org/00se2k293","country_code":"TW","type":"education","lineage":["https://openalex.org/I148366613"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Jen-Hui Chuang","raw_affiliation_strings":["Department of Computer Science, National Chiao Tung University, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, National Chiao Tung University, Taiwan","institution_ids":["https://openalex.org/I148366613"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5031784635","display_name":"I-Chun Liao","orcid":null},"institutions":[{"id":"https://openalex.org/I148366613","display_name":"National Yang Ming Chiao Tung University","ror":"https://ror.org/00se2k293","country_code":"TW","type":"education","lineage":["https://openalex.org/I148366613"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"I-Chun Liao","raw_affiliation_strings":["Department of Computer Science, National Chiao Tung University, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, National Chiao Tung University, Taiwan","institution_ids":["https://openalex.org/I148366613"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.2485,"has_fulltext":false,"cited_by_count":31,"citation_normalized_percentile":{"value":0.84939837,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1917","last_page":"1921"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","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/T10036","display_name":"Advanced Neural Network Applications","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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9980000257492065,"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/aerial-image","display_name":"Aerial image","score":0.8253902792930603},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.8047443628311157},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.7246434688568115},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.7133280634880066},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7031869292259216},{"id":"https://openalex.org/keywords/aerial-imagery","display_name":"Aerial imagery","score":0.6458304524421692},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6382962465286255},{"id":"https://openalex.org/keywords/pascal","display_name":"Pascal (unit)","score":0.6224911212921143},{"id":"https://openalex.org/keywords/drone","display_name":"Drone","score":0.593011200428009},{"id":"https://openalex.org/keywords/pedestrian-detection","display_name":"Pedestrian detection","score":0.5688948631286621},{"id":"https://openalex.org/keywords/vanishing-point","display_name":"Vanishing point","score":0.5442526340484619},{"id":"https://openalex.org/keywords/perspective","display_name":"Perspective (graphical)","score":0.5191511511802673},{"id":"https://openalex.org/keywords/transformation","display_name":"Transformation (genetics)","score":0.4924212694168091},{"id":"https://openalex.org/keywords/pedestrian","display_name":"Pedestrian","score":0.31657537817955017},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3014686703681946},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2938147187232971},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.2534026503562927}],"concepts":[{"id":"https://openalex.org/C2776429412","wikidata":"https://www.wikidata.org/wiki/Q4688011","display_name":"Aerial image","level":3,"score":0.8253902792930603},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8047443628311157},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.7246434688568115},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7133280634880066},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7031869292259216},{"id":"https://openalex.org/C2987819851","wikidata":"https://www.wikidata.org/wiki/Q191839","display_name":"Aerial imagery","level":2,"score":0.6458304524421692},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6382962465286255},{"id":"https://openalex.org/C75608658","wikidata":"https://www.wikidata.org/wiki/Q44395","display_name":"Pascal (unit)","level":2,"score":0.6224911212921143},{"id":"https://openalex.org/C59519942","wikidata":"https://www.wikidata.org/wiki/Q650665","display_name":"Drone","level":2,"score":0.593011200428009},{"id":"https://openalex.org/C2780156472","wikidata":"https://www.wikidata.org/wiki/Q2355550","display_name":"Pedestrian detection","level":3,"score":0.5688948631286621},{"id":"https://openalex.org/C99404194","wikidata":"https://www.wikidata.org/wiki/Q163362","display_name":"Vanishing point","level":3,"score":0.5442526340484619},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.5191511511802673},{"id":"https://openalex.org/C204241405","wikidata":"https://www.wikidata.org/wiki/Q461499","display_name":"Transformation (genetics)","level":3,"score":0.4924212694168091},{"id":"https://openalex.org/C2777113093","wikidata":"https://www.wikidata.org/wiki/Q221488","display_name":"Pedestrian","level":2,"score":0.31657537817955017},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3014686703681946},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2938147187232971},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.2534026503562927},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"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/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip.2018.8451144","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2018.8451144","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 25th IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","score":0.6700000166893005,"display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1536680647","https://openalex.org/W1988635366","https://openalex.org/W2004528855","https://openalex.org/W2031489346","https://openalex.org/W2102605133","https://openalex.org/W2117539524","https://openalex.org/W2119821739","https://openalex.org/W2161969291","https://openalex.org/W2163605009","https://openalex.org/W2168356304","https://openalex.org/W2570343428","https://openalex.org/W2963037989","https://openalex.org/W3106250896","https://openalex.org/W4239510810","https://openalex.org/W6647426982","https://openalex.org/W6684191040","https://openalex.org/W6785652829"],"related_works":["https://openalex.org/W4313315626","https://openalex.org/W4283696875","https://openalex.org/W3110585990","https://openalex.org/W4385767632","https://openalex.org/W2898690910","https://openalex.org/W2784132289","https://openalex.org/W4286697184","https://openalex.org/W2889700547","https://openalex.org/W3034139063","https://openalex.org/W2889866244"],"abstract_inverted_index":{"Drones":[0],"are":[1,61],"well-liked":[2],"nowadays.":[3],"However,":[4],"deep":[5,111],"learning":[6,112],"models":[7],"for":[8,17,109],"object":[9,46],"detection":[10,15,106],"still":[11],"cannot":[12],"have":[13],"high":[14,27],"rates":[16,107],"pedestrians":[18,72],"in":[19,47,58,76],"aerial":[20,37,48,59,77],"images":[21,49,60],"even":[22],"though":[23],"they":[24],"already":[25],"show":[26],"precision":[28],"on":[29],"PASCAL":[30],"VOC":[31],"2007.":[32],"The":[33],"main":[34],"challenges":[35],"of":[36,44],"image":[38,84],"analysis":[39],"include:":[40],"(i)":[41],"the":[42,56,71,92,105],"size":[43],"an":[45],"can":[50,102],"be":[51],"very":[52],"small,":[53],"and":[54,86],"(ii)":[55],"objects":[57],"tilted":[62],"outward":[63],"due":[64],"to":[65,74,90],"perspective":[66],"projection":[67],"deformation,":[68],"which":[69],"make":[70],"hard":[73],"recognize":[75],"images.":[78],"In":[79],"this":[80],"paper,":[81],"we":[82],"utilize":[83],"partition":[85],"vanishing":[87],"point":[88],"transformation":[89],"overcome":[91],"above":[93],"challenges.":[94],"Experimental":[95],"results":[96],"demonstrate":[97],"that":[98],"such":[99],"pre-processing":[100],"methods":[101],"indeed":[103],"increase":[104],"significantly":[108],"some":[110],"models.":[113]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":2}],"updated_date":"2026-03-29T06:01:01.467347","created_date":"2025-10-10T00:00:00"}
