{"id":"https://openalex.org/W2781371121","doi":"https://doi.org/10.1109/dicta.2017.8227421","title":"Counting People Based on Linear, Weighted, and Local Random Forests","display_name":"Counting People Based on Linear, Weighted, and Local Random Forests","publication_year":2017,"publication_date":"2017-11-01","ids":{"openalex":"https://openalex.org/W2781371121","doi":"https://doi.org/10.1109/dicta.2017.8227421","mag":"2781371121"},"language":"en","primary_location":{"id":"doi:10.1109/dicta.2017.8227421","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dicta.2017.8227421","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 International Conference on Digital Image Computing: Techniques and Applications (DICTA)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://opus.lib.uts.edu.au/bitstream/10453/119925/4/OCC-106738_AM.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5061035607","display_name":"Helia Farhood","orcid":"https://orcid.org/0000-0001-8213-2338"},"institutions":[{"id":"https://openalex.org/I114017466","display_name":"University of Technology Sydney","ror":"https://ror.org/03f0f6041","country_code":"AU","type":"education","lineage":["https://openalex.org/I114017466"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Helia Farhood","raw_affiliation_strings":["Global Big Data Technologies Centre, University of Technology Sydney, Sydney, Australia"],"affiliations":[{"raw_affiliation_string":"Global Big Data Technologies Centre, University of Technology Sydney, Sydney, Australia","institution_ids":["https://openalex.org/I114017466"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006921134","display_name":"Xiangjian He","orcid":"https://orcid.org/0000-0001-8962-540X"},"institutions":[{"id":"https://openalex.org/I114017466","display_name":"University of Technology Sydney","ror":"https://ror.org/03f0f6041","country_code":"AU","type":"education","lineage":["https://openalex.org/I114017466"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Xiangjian He","raw_affiliation_strings":["Global Big Data Technologies Centre, University of Technology Sydney, Sydney, Australia"],"affiliations":[{"raw_affiliation_string":"Global Big Data Technologies Centre, University of Technology Sydney, Sydney, Australia","institution_ids":["https://openalex.org/I114017466"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100395314","display_name":"Wenjing Jia","orcid":"https://orcid.org/0000-0002-0940-3338"},"institutions":[{"id":"https://openalex.org/I114017466","display_name":"University of Technology Sydney","ror":"https://ror.org/03f0f6041","country_code":"AU","type":"education","lineage":["https://openalex.org/I114017466"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Wenjing Jia","raw_affiliation_strings":["Global Big Data Technologies Centre, University of Technology Sydney, Sydney, Australia"],"affiliations":[{"raw_affiliation_string":"Global Big Data Technologies Centre, University of Technology Sydney, Sydney, Australia","institution_ids":["https://openalex.org/I114017466"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114032796","display_name":"Michael Blumenstein","orcid":null},"institutions":[{"id":"https://openalex.org/I114017466","display_name":"University of Technology Sydney","ror":"https://ror.org/03f0f6041","country_code":"AU","type":"education","lineage":["https://openalex.org/I114017466"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Michael Blumenstein","raw_affiliation_strings":["Centre for Artificial Intelligence, University of Technology Sydney, Sydney, Australia"],"affiliations":[{"raw_affiliation_string":"Centre for Artificial Intelligence, University of Technology Sydney, Sydney, Australia","institution_ids":["https://openalex.org/I114017466"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5028780369","display_name":"Hanhui Li","orcid":"https://orcid.org/0000-0002-9838-6532"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hanhui Li","raw_affiliation_strings":["School of Data and Computer Science, Sun Yat-sen University, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Data and Computer Science, Sun Yat-sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5061035607"],"corresponding_institution_ids":["https://openalex.org/I114017466"],"apc_list":null,"apc_paid":null,"fwci":0.3697,"has_fulltext":true,"cited_by_count":15,"citation_normalized_percentile":{"value":0.7065874,"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":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":1.0,"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":1.0,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9883999824523926,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9793999791145325,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.7336151599884033},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7116945385932922},{"id":"https://openalex.org/keywords/perspective","display_name":"Perspective (graphical)","score":0.6687249541282654},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.6312466859817505},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.614952564239502},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.5308569073677063},{"id":"https://openalex.org/keywords/transformation","display_name":"Transformation (genetics)","score":0.5109754800796509},{"id":"https://openalex.org/keywords/linear-regression","display_name":"Linear regression","score":0.4633384943008423},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.43398240208625793},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.35564857721328735},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3444092273712158},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.32321423292160034},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.20856136083602905},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.15931448340415955},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.09095591306686401}],"concepts":[{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.7336151599884033},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7116945385932922},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.6687249541282654},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.6312466859817505},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.614952564239502},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.5308569073677063},{"id":"https://openalex.org/C204241405","wikidata":"https://www.wikidata.org/wiki/Q461499","display_name":"Transformation (genetics)","level":3,"score":0.5109754800796509},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.4633384943008423},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.43398240208625793},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.35564857721328735},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3444092273712158},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.32321423292160034},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.20856136083602905},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15931448340415955},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.09095591306686401},{"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/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/dicta.2017.8227421","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dicta.2017.8227421","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 International Conference on Digital Image Computing: Techniques and Applications (DICTA)","raw_type":"proceedings-article"},{"id":"pmh:oai:opus.lib.uts.edu.au:10453/119925","is_oa":true,"landing_page_url":"http://hdl.handle.net/10453/119925","pdf_url":"https://opus.lib.uts.edu.au/bitstream/10453/119925/4/OCC-106738_AM.pdf","source":{"id":"https://openalex.org/S4306401357","display_name":"UTS ePRESS (University of Technology Sydney)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I114017466","host_organization_name":"University of Technology Sydney","host_organization_lineage":["https://openalex.org/I114017466"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference Proceeding"}],"best_oa_location":{"id":"pmh:oai:opus.lib.uts.edu.au:10453/119925","is_oa":true,"landing_page_url":"http://hdl.handle.net/10453/119925","pdf_url":"https://opus.lib.uts.edu.au/bitstream/10453/119925/4/OCC-106738_AM.pdf","source":{"id":"https://openalex.org/S4306401357","display_name":"UTS ePRESS (University of Technology Sydney)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I114017466","host_organization_name":"University of Technology Sydney","host_organization_lineage":["https://openalex.org/I114017466"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference Proceeding"},"sustainable_development_goals":[{"display_name":"Life in Land","score":0.7099999785423279,"id":"https://metadata.un.org/sdg/15"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2781371121.pdf","grobid_xml":"https://content.openalex.org/works/W2781371121.grobid-xml"},"referenced_works_count":36,"referenced_works":["https://openalex.org/W94414152","https://openalex.org/W179668148","https://openalex.org/W1531249942","https://openalex.org/W1542079534","https://openalex.org/W1581937791","https://openalex.org/W1910776219","https://openalex.org/W1976959044","https://openalex.org/W1978531778","https://openalex.org/W1992802489","https://openalex.org/W2042322506","https://openalex.org/W2066099897","https://openalex.org/W2073539418","https://openalex.org/W2075875861","https://openalex.org/W2096229530","https://openalex.org/W2109064712","https://openalex.org/W2120815373","https://openalex.org/W2123175289","https://openalex.org/W2125095437","https://openalex.org/W2143043044","https://openalex.org/W2145983039","https://openalex.org/W2151103935","https://openalex.org/W2155916750","https://openalex.org/W2160624808","https://openalex.org/W2161841955","https://openalex.org/W2164990725","https://openalex.org/W2207893099","https://openalex.org/W2463631526","https://openalex.org/W2541952933","https://openalex.org/W4285719527","https://openalex.org/W4290994097","https://openalex.org/W6603793584","https://openalex.org/W6607331729","https://openalex.org/W6632569617","https://openalex.org/W6678246861","https://openalex.org/W6681368121","https://openalex.org/W6684039954"],"related_works":["https://openalex.org/W2048488252","https://openalex.org/W4289884158","https://openalex.org/W2940614149","https://openalex.org/W4288365262","https://openalex.org/W2787485953","https://openalex.org/W3217432596","https://openalex.org/W31220157","https://openalex.org/W2288557197","https://openalex.org/W4233024177","https://openalex.org/W2101914902"],"abstract_inverted_index":{"Recently,":[0],"many":[1,21],"works":[2],"have":[3,19],"been":[4],"published":[5],"for":[6,60,93],"counting":[7,61,94],"people.":[8],"However,":[9],"when":[10],"being":[11],"applied":[12],"to":[13,24,96],"real-world":[14],"train":[15,126],"station":[16,68],"videos,":[17],"they":[18],"exposed":[20],"limitations":[22],"due":[23],"problems":[25,100],"such":[26],"as":[27,83,85],"low":[28],"resolution,":[29],"heavy":[30],"occlusion,":[31],"various":[32],"density":[33,47],"levels":[34],"and":[35,76,117,142],"perspective":[36,99],"distortions.":[37],"In":[38],"this":[39],"paper,":[40],"following":[41],"the":[42,98,102,114,136],"recent":[43,111],"trend":[44],"of":[45,101,120],"regression-based":[46],"estimation,":[48],"we":[49,88],"present":[50,107],"a":[51,90,118,125],"linear":[52,91],"regression":[53],"approach":[54],"based":[55,139],"on":[56,67,113,140],"local":[57],"Random":[58],"Forests":[59],"either":[62],"standing":[63],"or":[64],"moving":[65],"people":[66,95],"platforms.":[69],"By":[70],"dividing":[71],"each":[72],"frame":[73],"into":[74],"sub-windows":[75],"extracting":[77],"features":[78],"with":[79,135],"ground":[80],"truth":[81],"densities":[82],"well":[84],"learned":[86],"weights,":[87],"perform":[89],"transformation":[92],"overcome":[97],"existing":[103],"patch-based":[104],"approaches.":[105],"We":[106,128],"improvements":[108,131],"against":[109],"several":[110],"baselines":[112],"UCSD":[115],"dataset":[116,119],"CCTV":[121],"videos":[122],"taken":[123],"from":[124],"station.":[127],"also":[129],"show":[130],"in":[132],"speed":[133],"compared":[134],"state-of-the-art":[137],"models":[138],"detection":[141],"Deep":[143],"Learning.":[144]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":2},{"year":2018,"cited_by_count":2}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}