{"id":"https://openalex.org/W1977319067","doi":"https://doi.org/10.1145/2671188.2749331","title":"Extracting 3D Trajectories of Objects from 2D Videos using Particle Filter","display_name":"Extracting 3D Trajectories of Objects from 2D Videos using Particle Filter","publication_year":2015,"publication_date":"2015-06-22","ids":{"openalex":"https://openalex.org/W1977319067","doi":"https://doi.org/10.1145/2671188.2749331","mag":"1977319067"},"language":"en","primary_location":{"id":"doi:10.1145/2671188.2749331","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2671188.2749331","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 5th ACM on International Conference on Multimedia Retrieval","raw_type":"proceedings-article"},"type":"conference-paper","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/A5052763223","display_name":"Zeyd Boukhers","orcid":"https://orcid.org/0000-0001-9778-9164"},"institutions":[{"id":"https://openalex.org/I206895457","display_name":"University of Siegen","ror":"https://ror.org/02azyry73","country_code":"DE","type":"education","lineage":["https://openalex.org/I206895457"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Zeyd Boukhers","raw_affiliation_strings":["University of Siegen, Siegen, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Siegen, Siegen, Germany","institution_ids":["https://openalex.org/I206895457"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013527575","display_name":"Kimiaki Shirahama","orcid":"https://orcid.org/0000-0003-1843-5152"},"institutions":[{"id":"https://openalex.org/I206895457","display_name":"University of Siegen","ror":"https://ror.org/02azyry73","country_code":"DE","type":"education","lineage":["https://openalex.org/I206895457"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Kimiaki Shirahama","raw_affiliation_strings":["University of Siegen, Siegen, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Siegen, Siegen, Germany","institution_ids":["https://openalex.org/I206895457"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025793704","display_name":"Fr\u00e9d\u00e9ric Li","orcid":"https://orcid.org/0000-0003-2110-4207"},"institutions":[{"id":"https://openalex.org/I201181511","display_name":"\u00c9cole Nationale Sup\u00e9rieure de Techniques Avanc\u00e9es","ror":"https://ror.org/0309cs235","country_code":"FR","type":"education","lineage":["https://openalex.org/I201181511","https://openalex.org/I4210145102"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Fr\u00e9d\u00e9ric Li","raw_affiliation_strings":["\u00c9cole Nationale Sup\u00e9rieure de Techniques Avanc\u00e9es, Paris, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"\u00c9cole Nationale Sup\u00e9rieure de Techniques Avanc\u00e9es, Paris, France","institution_ids":["https://openalex.org/I201181511"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5037990310","display_name":"Marcin Grzegorzek","orcid":"https://orcid.org/0000-0003-4877-8287"},"institutions":[{"id":"https://openalex.org/I206895457","display_name":"University of Siegen","ror":"https://ror.org/02azyry73","country_code":"DE","type":"education","lineage":["https://openalex.org/I206895457"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Marcin Grzegorzek","raw_affiliation_strings":["University of Siegen, Siegen, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Siegen, Siegen, Germany","institution_ids":["https://openalex.org/I206895457"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.1352,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.40931242,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"83","last_page":"90"},"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/T10531","display_name":"Advanced Vision and Imaging","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":0.9994999766349792,"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/computer-vision","display_name":"Computer vision","score":0.8046705722808838},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7611678838729858},{"id":"https://openalex.org/keywords/particle-filter","display_name":"Particle filter","score":0.709449827671051},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6709283590316772},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.6670589447021484},{"id":"https://openalex.org/keywords/position","display_name":"Position (finance)","score":0.6387078762054443},{"id":"https://openalex.org/keywords/video-tracking","display_name":"Video tracking","score":0.512356162071228},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.5117535591125488},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.501685619354248},{"id":"https://openalex.org/keywords/image-plane","display_name":"Image plane","score":0.42542314529418945},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3312857747077942},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.29541710019111633}],"concepts":[{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.8046705722808838},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7611678838729858},{"id":"https://openalex.org/C52421305","wikidata":"https://www.wikidata.org/wiki/Q1151499","display_name":"Particle filter","level":3,"score":0.709449827671051},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6709283590316772},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.6670589447021484},{"id":"https://openalex.org/C198082294","wikidata":"https://www.wikidata.org/wiki/Q3399648","display_name":"Position (finance)","level":2,"score":0.6387078762054443},{"id":"https://openalex.org/C202474056","wikidata":"https://www.wikidata.org/wiki/Q1931635","display_name":"Video tracking","level":3,"score":0.512356162071228},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.5117535591125488},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.501685619354248},{"id":"https://openalex.org/C120515352","wikidata":"https://www.wikidata.org/wiki/Q2564580","display_name":"Image plane","level":3,"score":0.42542314529418945},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3312857747077942},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.29541710019111633},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2671188.2749331","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2671188.2749331","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 5th ACM on International Conference on Multimedia Retrieval","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W659382331","https://openalex.org/W1545195129","https://openalex.org/W1686810756","https://openalex.org/W1972283961","https://openalex.org/W1986844695","https://openalex.org/W1989560997","https://openalex.org/W1998613121","https://openalex.org/W2000852493","https://openalex.org/W2011286667","https://openalex.org/W2016387968","https://openalex.org/W2046777839","https://openalex.org/W2060280062","https://openalex.org/W2060451775","https://openalex.org/W2062903088","https://openalex.org/W2074254947","https://openalex.org/W2080920426","https://openalex.org/W2090518410","https://openalex.org/W2093655440","https://openalex.org/W2104706722","https://openalex.org/W2110121771","https://openalex.org/W2112440615","https://openalex.org/W2113926057","https://openalex.org/W2117082993","https://openalex.org/W2117539524","https://openalex.org/W2122190623","https://openalex.org/W2123595601","https://openalex.org/W2124384194","https://openalex.org/W2130660124","https://openalex.org/W2132947399","https://openalex.org/W2139905387","https://openalex.org/W2141166208","https://openalex.org/W2141355815","https://openalex.org/W2147953023","https://openalex.org/W2149705965","https://openalex.org/W2151047074","https://openalex.org/W2160337655","https://openalex.org/W2168356304","https://openalex.org/W2535579907","https://openalex.org/W2952020226","https://openalex.org/W3145294510","https://openalex.org/W4206814933"],"related_works":["https://openalex.org/W2015530857","https://openalex.org/W2556064263","https://openalex.org/W1991846142","https://openalex.org/W1583020711","https://openalex.org/W1521151968","https://openalex.org/W1994458110","https://openalex.org/W2100525497","https://openalex.org/W2965594636","https://openalex.org/W2912550626","https://openalex.org/W2011062627"],"abstract_inverted_index":{"Depth":[0],"estimation":[1,33,78,143],"is":[2,19,86,112,167],"a":[3,11,28,161,170],"method":[4],"to":[5,173],"estimate":[6],"the":[7,15,35,46,52,83,87,101,104,127,134,137,141,151,154,165,182],"depth":[8,32,77,142],"information":[9],"in":[10,34,51,153],"2D":[12,176],"image/video,":[13],"where":[14,38,160],"original":[16],"3D":[17,41,53,56,73,128,155,162],"space":[18,156],"projected":[20],"onto":[21],"an":[22,49,108,131],"image":[23],"plane.":[24],"This":[25],"paper":[26],"introduces":[27],"novel":[29],"extension":[30],"of":[31,48,103,130,164,184],"video":[36,67],"domain,":[37],"we":[39,71,124,149],"extract":[40,72],"trajectories":[42,57,74],"which":[43],"individually":[44],"represent":[45],"transition":[47],"object":[50,64,80,109,132,145,152,166],"space.":[54],"Such":[55],"are":[58],"useful":[59],"for":[60,66,100],"appropriately":[61,113],"characterising":[62],"spatio-temporal":[63],"relations":[65],"event":[68],"detection.":[69],"While":[70],"by":[75,115],"combining":[76],"and":[79,107,144],"detection":[81,146],"results,":[82],"major":[84],"problem":[85],"inconsistency":[88],"between":[89,140],"these":[90],"results.":[91,147],"For":[92],"example,":[93],"significantly":[94],"different":[95],"depths":[96,117],"may":[97,118],"be":[98,119],"estimated":[99,116],"region":[102,110],"same":[105],"object,":[106],"that":[111],"shaped":[114],"missed.":[120],"To":[121],"overcome":[122],"this,":[123],"first":[125],"initialise":[126],"position":[129,163],"using":[133,157],"frame":[135],"with":[136],"highest":[138],"consistency":[139],"Then,":[148],"track":[150],"particle":[158],"filter,":[159],"modelled":[168],"as":[169],"hidden":[171],"state":[172],"generate":[174],"its":[175],"visual":[177],"appearance.":[178],"Experimental":[179],"results":[180],"demonstrate":[181],"effectiveness":[183],"our":[185],"method.":[186]},"counts_by_year":[{"year":2017,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
