{"id":"https://openalex.org/W3008955098","doi":"https://doi.org/10.1145/3381271.3381292","title":"Automatic bounding-box-labeling method of occluded objects in virtual image data","display_name":"Automatic bounding-box-labeling method of occluded objects in virtual image data","publication_year":2020,"publication_date":"2020-01-10","ids":{"openalex":"https://openalex.org/W3008955098","doi":"https://doi.org/10.1145/3381271.3381292","mag":"3008955098"},"language":"en","primary_location":{"id":"doi:10.1145/3381271.3381292","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3381271.3381292","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 International Conference on Multimedia and Image Processing","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/A5100408892","display_name":"Xinyue Wang","orcid":"https://orcid.org/0009-0005-3851-5768"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xinyue Wang","raw_affiliation_strings":["Beijing University of Posts and Telecommunication"],"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunication","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101741512","display_name":"Lingzhong Meng","orcid":"https://orcid.org/0000-0003-4463-2192"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lingzhong Meng","raw_affiliation_strings":["Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5076010472","display_name":"Yunzhi Xue","orcid":null},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yunzhi Xue","raw_affiliation_strings":["Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100408892"],"corresponding_institution_ids":["https://openalex.org/I139759216"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.01688849,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"163","last_page":"168"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9958000183105469,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9958000183105469,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9944000244140625,"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/T12923","display_name":"Digital Image Processing Techniques","score":0.9940000176429749,"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/minimum-bounding-box","display_name":"Minimum bounding box","score":0.9175589084625244},{"id":"https://openalex.org/keywords/bounding-overwatch","display_name":"Bounding overwatch","score":0.74496990442276},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7062495946884155},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.6120486259460449},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6100753545761108},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5396485328674316},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5098192095756531},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5063360929489136},{"id":"https://openalex.org/keywords/computer-graphics","display_name":"Computer graphics","score":0.4998202323913574},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.43072181940078735},{"id":"https://openalex.org/keywords/binary-number","display_name":"Binary number","score":0.425433874130249},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.20332679152488708}],"concepts":[{"id":"https://openalex.org/C147037132","wikidata":"https://www.wikidata.org/wiki/Q6865426","display_name":"Minimum bounding box","level":3,"score":0.9175589084625244},{"id":"https://openalex.org/C63584917","wikidata":"https://www.wikidata.org/wiki/Q333286","display_name":"Bounding overwatch","level":2,"score":0.74496990442276},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7062495946884155},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.6120486259460449},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6100753545761108},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5396485328674316},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5098192095756531},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5063360929489136},{"id":"https://openalex.org/C77660652","wikidata":"https://www.wikidata.org/wiki/Q150971","display_name":"Computer graphics","level":2,"score":0.4998202323913574},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.43072181940078735},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.425433874130249},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.20332679152488708},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3381271.3381292","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3381271.3381292","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 International Conference on Multimedia and Image Processing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Partnerships for the goals","id":"https://metadata.un.org/sdg/17","score":0.4000000059604645}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":6,"referenced_works":["https://openalex.org/W2771784662","https://openalex.org/W2890319410","https://openalex.org/W2944527105","https://openalex.org/W2948962821","https://openalex.org/W2957667237","https://openalex.org/W2963064196"],"related_works":["https://openalex.org/W4237171675","https://openalex.org/W3036286480","https://openalex.org/W4287027631","https://openalex.org/W3192357901","https://openalex.org/W2387360586","https://openalex.org/W2952736415","https://openalex.org/W3209723314","https://openalex.org/W3205398323","https://openalex.org/W2883297582","https://openalex.org/W4390524233"],"abstract_inverted_index":{"Computer":[0],"vision":[1],"technology":[2],"is":[3,20],"widely":[4],"used":[5,114],"based":[6,59,103],"on":[7,60,104],"its":[8],"massive":[9],"and":[10,50,76,93,151,155,175],"correct":[11],"data":[12,32,138],"set,":[13],"of":[14,29,48,82,149],"which":[15,64],"the":[16,70,79,86,105,117,121,137,159,168,172,178],"bounding":[17,62,80],"box":[18,81],"labeling":[19],"a":[21,26,56],"common":[22],"method.":[23],"Aimed":[24],"at":[25],"large":[27],"number":[28],"original":[30],"image":[31],"set":[33,139],"produced":[34,72],"by":[35,55,73,146],"virtual":[36,74],"simulation,":[37],"we":[38],"proposed":[39],"an":[40,109],"automatic":[41],"pixel-level":[42],"bounding-box-labeling":[43,126],"method":[44,53,87,165],"to":[45,68,98,115,128,133,153],"solve":[46,167],"problem":[47,170],"accuracy":[49],"speed.":[51],"The":[52],"starts":[54],"fundamental":[57],"algorithm":[58,97,111,127],"targeted":[61,130],"box,":[63],"will":[65,88],"be":[66,113],"adopted":[67],"label":[69,129,177],"images":[71,102],"simulation":[75],"learn":[77],"from":[78,140],"different":[83],"objects;":[84],"Next,":[85],"find":[89],"consistent":[90],"seed":[91,106],"points":[92],"apply":[94],"region":[95],"growing":[96],"automatically":[99],"produce":[100],"binary":[101,122],"points;":[107],"Then,":[108],"occlusion-estimating":[110],"can":[112,166,176],"evaluate":[116],"occluded":[118],"conditions":[119],"in":[120],"image;":[123],"Finally,":[124],"employ":[125],"objects":[131],"according":[132],"various":[134],"occlusion.":[135],"Apply":[136],"2019":[141],"Small":[142],"Target":[143],"Competition":[144],"held":[145],"China":[147],"Society":[148],"Images":[150],"Graphics":[152],"test":[154],"verify":[156],"our":[157],"method,":[158],"result":[160],"turns":[161],"out":[162],"that":[163],"this":[164],"occlusion":[169,174],"especially":[171],"truncate":[173],"objects'":[179],"entire":[180],"body":[181],"precisely.":[182]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
