{"id":"https://openalex.org/W2989625535","doi":"https://doi.org/10.1109/itsc.2019.8917175","title":"Real-World Trajectory Extraction from Aerial Videos - A Comprehensive and Effective Solution","display_name":"Real-World Trajectory Extraction from Aerial Videos - A Comprehensive and Effective Solution","publication_year":2019,"publication_date":"2019-10-01","ids":{"openalex":"https://openalex.org/W2989625535","doi":"https://doi.org/10.1109/itsc.2019.8917175","mag":"2989625535"},"language":"en","primary_location":{"id":"doi:10.1109/itsc.2019.8917175","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc.2019.8917175","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE Intelligent Transportation Systems Conference (ITSC)","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/A5101671477","display_name":"Dongfang Zhao","orcid":"https://orcid.org/0000-0002-0677-634X"},"institutions":[{"id":"https://openalex.org/I2613432","display_name":"University of South Florida","ror":"https://ror.org/032db5x82","country_code":"US","type":"education","lineage":["https://openalex.org/I2613432"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Dongfang Zhao","raw_affiliation_strings":["Department of Civil and Environmental Engineering, University of South Florida, FL"],"affiliations":[{"raw_affiliation_string":"Department of Civil and Environmental Engineering, University of South Florida, FL","institution_ids":["https://openalex.org/I2613432"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100355083","display_name":"Xiaopeng Li","orcid":"https://orcid.org/0000-0002-5264-3775"},"institutions":[{"id":"https://openalex.org/I2613432","display_name":"University of South Florida","ror":"https://ror.org/032db5x82","country_code":"US","type":"education","lineage":["https://openalex.org/I2613432"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiaopeng Li","raw_affiliation_strings":["Department of Civil and Environmental Engineering, University of South Florida, FL"],"affiliations":[{"raw_affiliation_string":"Department of Civil and Environmental Engineering, University of South Florida, FL","institution_ids":["https://openalex.org/I2613432"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5101671477"],"corresponding_institution_ids":["https://openalex.org/I2613432"],"apc_list":null,"apc_paid":null,"fwci":0.2024,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.55279215,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"2854","last_page":"2859"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9997000098228455,"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":0.9997000098228455,"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":0.9987000226974487,"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/T13282","display_name":"Automated Road and Building Extraction","score":0.9973000288009644,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean Engineering"},"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/computer-science","display_name":"Computer science","score":0.769461452960968},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.7453739643096924},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.7345840930938721},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7201376557350159},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.5674359798431396},{"id":"https://openalex.org/keywords/roundabout","display_name":"Roundabout","score":0.5595685839653015},{"id":"https://openalex.org/keywords/rotation","display_name":"Rotation (mathematics)","score":0.5554714798927307},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.5468513369560242},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.517096996307373},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.5061578154563904},{"id":"https://openalex.org/keywords/global-positioning-system","display_name":"Global Positioning System","score":0.446174681186676},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12070474028587341},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.10417434573173523}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.769461452960968},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7453739643096924},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.7345840930938721},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7201376557350159},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.5674359798431396},{"id":"https://openalex.org/C109157449","wikidata":"https://www.wikidata.org/wiki/Q7371221","display_name":"Roundabout","level":2,"score":0.5595685839653015},{"id":"https://openalex.org/C74050887","wikidata":"https://www.wikidata.org/wiki/Q848368","display_name":"Rotation (mathematics)","level":2,"score":0.5554714798927307},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.5468513369560242},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.517096996307373},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.5061578154563904},{"id":"https://openalex.org/C60229501","wikidata":"https://www.wikidata.org/wiki/Q18822","display_name":"Global Positioning System","level":2,"score":0.446174681186676},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12070474028587341},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.10417434573173523},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C19417346","wikidata":"https://www.wikidata.org/wiki/Q7922","display_name":"Pedagogy","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/itsc.2019.8917175","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc.2019.8917175","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE Intelligent Transportation Systems Conference (ITSC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6600000262260437,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W641020656","https://openalex.org/W1573546770","https://openalex.org/W1919099765","https://openalex.org/W1994304612","https://openalex.org/W1998613433","https://openalex.org/W2040441352","https://openalex.org/W2057483198","https://openalex.org/W2111876879","https://openalex.org/W2115415549","https://openalex.org/W2127070222","https://openalex.org/W2163145488","https://openalex.org/W2292973401","https://openalex.org/W2464624156","https://openalex.org/W2464708700","https://openalex.org/W2467828995","https://openalex.org/W2552864711","https://openalex.org/W2761568138","https://openalex.org/W2896642734","https://openalex.org/W2963150697","https://openalex.org/W3151739637","https://openalex.org/W4249848180","https://openalex.org/W6620980068","https://openalex.org/W6640334822","https://openalex.org/W6677106985","https://openalex.org/W6684080438","https://openalex.org/W6719012276"],"related_works":["https://openalex.org/W2093826578","https://openalex.org/W4294237266","https://openalex.org/W3195565206","https://openalex.org/W647040144","https://openalex.org/W2558143469","https://openalex.org/W2176704059","https://openalex.org/W3118850949","https://openalex.org/W4375811566","https://openalex.org/W2053055974","https://openalex.org/W4320802711"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3,68],"propose":[4],"an":[5],"advanced":[6,41],"real-world":[7,120],"trajectory":[8],"extraction":[9],"method":[10,19,84,113],"to":[11,49,118],"extract":[12,119],"vehicle":[13,23,106,122],"trajectories":[14,79,107,123],"from":[15,124],"aerial":[16,87,125],"videos.":[17,126],"The":[18,102,111],"includes":[20],"three":[21],"steps:":[22],"identification":[24],"and":[25,29,32,45,57,96],"tracking,":[26],"camera":[27,55],"rotation":[28,56],"shifting":[30,58],"correction,":[31],"semi-automatic":[33],"lane":[34,70],"identification.":[35],"We":[36,53,81],"identify":[37],"vehicles":[38,47],"using":[39,60,85],"the":[40,74,83],"Mask":[42],"R-CNN":[43],"model":[44],"track":[46],"according":[48],"their":[50],"movement":[51],"properties.":[52],"calculate":[54],"parameters":[59],"a":[61,115],"binary":[62],"search":[63],"correlation-based":[64],"matching":[65],"algorithm.":[66],"And":[67],"generate":[69],"structures":[71],"based":[72],"on":[73],"topographic":[75],"properties":[76],"of":[77,91],"extracted":[78,109],"semi-automatically.":[80],"tested":[82],"two":[86],"video":[88],"examples,":[89],"one":[90,98],"which":[92],"captures":[93,99],"freeway":[94],"traffic":[95],"another":[97],"roundabout":[100],"traffic.":[101],"results":[103],"show":[104],"that":[105],"are":[108],"accurately.":[110],"proposed":[112],"provides":[114],"promising":[116],"solution":[117],"long":[121]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}