{"id":"https://openalex.org/W4235414275","doi":"https://doi.org/10.1109/mfi.2012.6343012","title":"Robust visual tracking based on adaptive depth-color-cue integration using range sensor","display_name":"Robust visual tracking based on adaptive depth-color-cue integration using range sensor","publication_year":2012,"publication_date":"2012-09-01","ids":{"openalex":"https://openalex.org/W4235414275","doi":"https://doi.org/10.1109/mfi.2012.6343012"},"language":"en","primary_location":{"id":"doi:10.1109/mfi.2012.6343012","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mfi.2012.6343012","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI)","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/A5100428564","display_name":"Can Wang","orcid":"https://orcid.org/0000-0002-0914-3994"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Can Wang","raw_affiliation_strings":["Key Laboratory of Integrated Microsystems Shenzhen Graduate School, Peking University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Integrated Microsystems Shenzhen Graduate School, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100410326","display_name":"Hong Liu","orcid":"https://orcid.org/0000-0002-7498-6541"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hong Liu","raw_affiliation_strings":["Key Laboratory of Machine Perception and Intelligence, Shenzhen Graduate School, Peking University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Machine Perception and Intelligence, Shenzhen Graduate School, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5100428564"],"corresponding_institution_ids":["https://openalex.org/I20231570"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.39417094,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9991999864578247,"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":0.9991999864578247,"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/T11019","display_name":"Image Enhancement Techniques","score":0.9984999895095825,"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":0.9977999925613403,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.7894090414047241},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.7783977389335632},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.7428478598594666},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6807347536087036},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.6267008781433105},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.55661541223526},{"id":"https://openalex.org/keywords/mean-shift","display_name":"Mean-shift","score":0.519242525100708},{"id":"https://openalex.org/keywords/sensory-cue","display_name":"Sensory cue","score":0.4386536777019501},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.34915900230407715}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7894090414047241},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7783977389335632},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7428478598594666},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6807347536087036},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.6267008781433105},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.55661541223526},{"id":"https://openalex.org/C48548287","wikidata":"https://www.wikidata.org/wiki/Q6803557","display_name":"Mean-shift","level":3,"score":0.519242525100708},{"id":"https://openalex.org/C111370547","wikidata":"https://www.wikidata.org/wiki/Q7451120","display_name":"Sensory cue","level":2,"score":0.4386536777019501},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.34915900230407715},{"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/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/mfi.2012.6343012","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mfi.2012.6343012","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7","score":0.6000000238418579}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W76294903","https://openalex.org/W1652099438","https://openalex.org/W1741230646","https://openalex.org/W2004674224","https://openalex.org/W2010529405","https://openalex.org/W2035972836","https://openalex.org/W2036310903","https://openalex.org/W2049381231","https://openalex.org/W2096579040","https://openalex.org/W2116027296","https://openalex.org/W2122897069","https://openalex.org/W2137071952","https://openalex.org/W2157087525","https://openalex.org/W2168771524","https://openalex.org/W2168849647","https://openalex.org/W2565236631","https://openalex.org/W6603102435","https://openalex.org/W6662743017","https://openalex.org/W6678333049","https://openalex.org/W6680537942","https://openalex.org/W6731173134"],"related_works":["https://openalex.org/W4389116644","https://openalex.org/W2351488884","https://openalex.org/W2358580902","https://openalex.org/W2348934962","https://openalex.org/W2897637803","https://openalex.org/W2379834692","https://openalex.org/W2364097328","https://openalex.org/W2353915084","https://openalex.org/W3137627078","https://openalex.org/W2349927973"],"abstract_inverted_index":{"In":[0],"visual":[1],"tracking":[2,134],"field,":[3],"multi-cue":[4],"integration":[5,34],"has":[6],"been":[7],"researched":[8],"extensively,":[9],"but":[10],"only":[11],"color-based":[12],"method":[13,69],"still":[14],"suffers":[15],"from":[16],"illumination":[17],"changes,":[18],"color-similar":[19],"background":[20,109],"or":[21],"complete":[22],"occlusion.":[23],"To":[24],"overcome":[25],"these":[26],"shortages,":[27],"this":[28,132],"paper":[29],"presents":[30],"an":[31],"adaptive":[32],"depth-color-cue":[33],"framework":[35],"for":[36,47,59,118],"Mean-shift":[37,119],"tracking.":[38,79,120],"The":[39],"state-of-art":[40],"2D":[41],"rectangles":[42],"evolves":[43],"to":[44,72,87],"3D":[45],"cubes":[46],"representing":[48,60],"target":[49,61,106],"region,":[50],"and":[51,53,108,129],"depth":[52],"color":[54],"cues":[55,77,98],"are":[56,99,102,116],"combined":[57],"together":[58],"appearance.":[62],"Moreover,":[63],"a":[64,81],"novel":[65],"depth-data-based":[66],"motion":[67,76],"detection":[68],"is":[70,85],"introduced":[71],"get":[73],"more":[74],"reliable":[75,97],"during":[78],"Furthermore,":[80],"reliability":[82,128],"evaluation":[83],"function":[84],"proposed":[86],"tune":[88],"cues'":[89,112],"weights":[90],"based":[91],"on":[92],"the":[93,127],"assumption":[94],"that":[95],"most":[96,103],"those":[100],"which":[101],"discriminative":[104],"between":[105],"region":[107],"regions.":[110],"Finally,":[111],"probability":[113],"distribution":[114],"maps":[115],"integrated":[117],"Extensive":[121],"experiments":[122],"under":[123],"various":[124],"conditions":[125],"demonstrate":[126],"robustness":[130],"of":[131],"depth-color-integrated":[133],"framework.":[135]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
