{"id":"https://openalex.org/W2728700151","doi":"https://doi.org/10.1109/iwssip.2017.7965613","title":"Camera motion compensation from T-junctions in distance map skeleton","display_name":"Camera motion compensation from T-junctions in distance map skeleton","publication_year":2017,"publication_date":"2017-05-01","ids":{"openalex":"https://openalex.org/W2728700151","doi":"https://doi.org/10.1109/iwssip.2017.7965613","mag":"2728700151"},"language":"en","primary_location":{"id":"doi:10.1109/iwssip.2017.7965613","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iwssip.2017.7965613","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 Systems, Signals and Image Processing (IWSSIP)","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/A5081987316","display_name":"Charles Beumier","orcid":null},"institutions":[{"id":"https://openalex.org/I150517870","display_name":"Royal Military Academy","ror":"https://ror.org/02vmnye06","country_code":"BE","type":"education","lineage":["https://openalex.org/I150517870"]}],"countries":["BE"],"is_corresponding":true,"raw_author_name":"Charles Beumier","raw_affiliation_strings":["Signal & Image Centre, Royal Military Academy, Belgium"],"affiliations":[{"raw_affiliation_string":"Signal & Image Centre, Royal Military Academy, Belgium","institution_ids":["https://openalex.org/I150517870"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5086623349","display_name":"Xavier Neyt","orcid":"https://orcid.org/0000-0002-8992-3877"},"institutions":[{"id":"https://openalex.org/I150517870","display_name":"Royal Military Academy","ror":"https://ror.org/02vmnye06","country_code":"BE","type":"education","lineage":["https://openalex.org/I150517870"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Xavier Neyt","raw_affiliation_strings":["Signal & Image Centre, Royal Military Academy, 30 Avenue de la Renaissance 1000 Brussels, Belgium"],"affiliations":[{"raw_affiliation_string":"Signal & Image Centre, Royal Military Academy, 30 Avenue de la Renaissance 1000 Brussels, Belgium","institution_ids":["https://openalex.org/I150517870"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5081987316"],"corresponding_institution_ids":["https://openalex.org/I150517870"],"apc_list":null,"apc_paid":null,"fwci":0.091,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.44534319,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"7","issue":null,"first_page":"1","last_page":"5"},"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","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/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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.848166823387146},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.8144687414169312},{"id":"https://openalex.org/keywords/translation","display_name":"Translation (biology)","score":0.6481530070304871},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6316726207733154},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.539815366268158},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.47880062460899353},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.47381818294525146},{"id":"https://openalex.org/keywords/motion-field","display_name":"Motion field","score":0.4519096612930298},{"id":"https://openalex.org/keywords/displacement","display_name":"Displacement (psychology)","score":0.44489848613739014},{"id":"https://openalex.org/keywords/distance-transform","display_name":"Distance transform","score":0.43198662996292114},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.4260897636413574},{"id":"https://openalex.org/keywords/computer-graphics","display_name":"Computer graphics (images)","score":0.4245809018611908},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.4173014163970947},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4016607701778412},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.247613787651062}],"concepts":[{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.848166823387146},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8144687414169312},{"id":"https://openalex.org/C149364088","wikidata":"https://www.wikidata.org/wiki/Q185917","display_name":"Translation (biology)","level":4,"score":0.6481530070304871},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6316726207733154},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.539815366268158},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.47880062460899353},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.47381818294525146},{"id":"https://openalex.org/C124774092","wikidata":"https://www.wikidata.org/wiki/Q6917782","display_name":"Motion field","level":3,"score":0.4519096612930298},{"id":"https://openalex.org/C107551265","wikidata":"https://www.wikidata.org/wiki/Q1458245","display_name":"Displacement (psychology)","level":2,"score":0.44489848613739014},{"id":"https://openalex.org/C73621898","wikidata":"https://www.wikidata.org/wiki/Q2940504","display_name":"Distance transform","level":3,"score":0.43198662996292114},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.4260897636413574},{"id":"https://openalex.org/C121684516","wikidata":"https://www.wikidata.org/wiki/Q7600677","display_name":"Computer graphics (images)","level":1,"score":0.4245809018611908},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.4173014163970947},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4016607701778412},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.247613787651062},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","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/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C542102704","wikidata":"https://www.wikidata.org/wiki/Q183257","display_name":"Psychotherapist","level":1,"score":0.0},{"id":"https://openalex.org/C105580179","wikidata":"https://www.wikidata.org/wiki/Q188928","display_name":"Messenger RNA","level":3,"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/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","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":1,"locations":[{"id":"doi:10.1109/iwssip.2017.7965613","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iwssip.2017.7965613","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 Systems, Signals and Image Processing (IWSSIP)","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":0.5600000023841858}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W2012015807","https://openalex.org/W2024915064","https://openalex.org/W2069537876","https://openalex.org/W2106990937","https://openalex.org/W2109573991","https://openalex.org/W2130069875","https://openalex.org/W2147555557","https://openalex.org/W2151103935","https://openalex.org/W2167771098","https://openalex.org/W4231795354","https://openalex.org/W4300763926","https://openalex.org/W6679268829"],"related_works":["https://openalex.org/W1501297619","https://openalex.org/W2375480909","https://openalex.org/W2353314428","https://openalex.org/W2051456680","https://openalex.org/W2012019886","https://openalex.org/W2166090428","https://openalex.org/W2381021552","https://openalex.org/W2359614599","https://openalex.org/W2350806989","https://openalex.org/W2095536241"],"abstract_inverted_index":{"In":[0,47],"the":[1,13,17,36,79,82,88,106,112,127],"field":[2,124],"of":[3,16,62,87,105,117,129],"aerial":[4],"surveillance,":[5],"tracking":[6],"targets":[7],"in":[8,31,39,81,144],"images":[9,98,107],"is":[10,23,75,99],"complicated":[11],"by":[12,140],"possible":[14],"motion":[15],"camera,":[18],"especially":[19],"if":[20],"frame":[21],"differencing":[22],"used":[24],"to":[25,34,67],"detect":[26],"moving":[27,155],"objects.":[28],"We":[29],"propose":[30],"this":[32,48],"paper":[33],"exploit":[35],"high":[37],"similarity":[38],"sequences":[40,138],"acquired":[41],"from":[42,53],"a":[43,103,141,148,153],"nearly":[44],"static":[45,150],"camera.":[46],"case":[49],"distance":[50,63,83],"maps":[51],"grown":[52],"image":[54,95,137],"edge":[55],"points":[56],"share":[57],"many":[58],"similarities":[59],"and":[60,91,157],"T-junctions":[61],"map":[64],"skeletons":[65],"appear":[66],"offer":[68],"precisely":[69],"located":[70],"reference":[71],"points.":[72,120],"Each":[73],"T-junction":[74,119],"attributed":[76],"seven":[77],"features:":[78],"value":[80],"map,":[84],"three":[85],"orientations":[86],"junction":[89],"branches":[90],"R,":[92],"G,":[93],"B":[94],"intensities.":[96],"Registering":[97],"carried":[100],"out":[101],"on":[102,136],"division":[104],"into":[108],"tiles,":[109],"looking":[110],"for":[111,126],"dominant":[113],"translation":[114],"per":[115],"tile":[116],"matching":[118],"The":[121],"obtained":[122],"displacement":[123],"allow":[125],"compensation":[128],"small":[130],"camera":[131],"motion.":[132],"This":[133],"was":[134],"tested":[135],"captured":[139],"smartphone":[142],"held":[143],"hand":[145],"while":[146],"targeting":[147],"given":[149],"scene":[151],"with":[152],"few":[154],"vehicles":[156],"pedestrians.":[158]},"counts_by_year":[{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}