{"id":"https://openalex.org/W2161950332","doi":"https://doi.org/10.1109/icip.2007.4379285","title":"Collaborative Mean Shift Tracking Based on Multi-Cue Integration and Auxiliary Objects","display_name":"Collaborative Mean Shift Tracking Based on Multi-Cue Integration and Auxiliary Objects","publication_year":2007,"publication_date":"2007-01-01","ids":{"openalex":"https://openalex.org/W2161950332","doi":"https://doi.org/10.1109/icip.2007.4379285","mag":"2161950332"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2007.4379285","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2007.4379285","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2007 IEEE International Conference on 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/A5100410286","display_name":"Hong Liu","orcid":"https://orcid.org/0000-0002-0896-8409"},"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":"Hong Liu","raw_affiliation_strings":["State Key Laboratory of Machine Perception, Shenzhen Graduate School, Peking University, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Machine Perception, Shenzhen Graduate School, Peking University, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100351961","display_name":"Lin Zhang","orcid":"https://orcid.org/0000-0003-4407-7678"},"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":"Lin Zhang","raw_affiliation_strings":["State Key Laboratory of Machine Perception, Shenzhen Graduate School, Peking University, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Machine Perception, Shenzhen Graduate School, Peking University, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081218523","display_name":"Ze Yu","orcid":"https://orcid.org/0000-0002-0177-5057"},"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":"Ze Yu","raw_affiliation_strings":["State Key Laboratory of Machine Perception, Shenzhen Graduate School, Peking University, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Machine Perception, Shenzhen Graduate School, Peking University, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017031914","display_name":"Hongbin Zha","orcid":"https://orcid.org/0000-0001-5860-4673"},"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":"Hongbin Zha","raw_affiliation_strings":["State Key Laboratory of Machine Perception, Shenzhen Graduate School, Peking University, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Machine Perception, Shenzhen Graduate School, Peking University, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102001806","display_name":"Ying Shi","orcid":"https://orcid.org/0000-0002-6495-305X"},"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":"Ying Shi","raw_affiliation_strings":["State Key Laboratory of Machine Perception, Shenzhen Graduate School, Peking University, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Machine Perception, Shenzhen Graduate School, Peking University, China","institution_ids":["https://openalex.org/I20231570"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100410286"],"corresponding_institution_ids":["https://openalex.org/I20231570"],"apc_list":null,"apc_paid":null,"fwci":2.5965,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.90822727,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"2","issue":null,"first_page":"III ","last_page":" 217"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9998000264167786,"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"}},"topics":[{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","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/T11019","display_name":"Image Enhancement Techniques","score":0.9810000061988831,"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/T12389","display_name":"Infrared Target Detection Methodologies","score":0.9761000275611877,"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/robustness","display_name":"Robustness (evolution)","score":0.7735735177993774},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7193864583969116},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.7103993892669678},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6760336756706238},{"id":"https://openalex.org/keywords/mean-shift","display_name":"Mean-shift","score":0.6708085536956787},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.666179358959198},{"id":"https://openalex.org/keywords/video-tracking","display_name":"Video tracking","score":0.5120683312416077},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.3896195590496063},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3181114196777344}],"concepts":[{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7735735177993774},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7193864583969116},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7103993892669678},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6760336756706238},{"id":"https://openalex.org/C48548287","wikidata":"https://www.wikidata.org/wiki/Q6803557","display_name":"Mean-shift","level":3,"score":0.6708085536956787},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.666179358959198},{"id":"https://openalex.org/C202474056","wikidata":"https://www.wikidata.org/wiki/Q1931635","display_name":"Video tracking","level":3,"score":0.5120683312416077},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.3896195590496063},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3181114196777344},{"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},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"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/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip.2007.4379285","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2007.4379285","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2007 IEEE International Conference on Image Processing","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":12,"referenced_works":["https://openalex.org/W1502024436","https://openalex.org/W1513768190","https://openalex.org/W1899675034","https://openalex.org/W2033009866","https://openalex.org/W2064707019","https://openalex.org/W2099963236","https://openalex.org/W2111919691","https://openalex.org/W2131393045","https://openalex.org/W2159128898","https://openalex.org/W2161406034","https://openalex.org/W6630587866","https://openalex.org/W6639557929"],"related_works":["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/W1487824918","https://openalex.org/W2386156666","https://openalex.org/W2349207614"],"abstract_inverted_index":{"Colour-based":[0],"mean":[1,50],"shift":[2,51],"is":[3,15,53],"an":[4],"effective":[5,89],"and":[6,20,39,95,136],"fast":[7],"algorithm":[8],"for":[9,25],"tracking":[10,33,141],"colour":[11],"blobs.":[12],"However,":[13],"it":[14],"vulnerable":[16],"to":[17,42,55,71,81,110],"full":[18],"occlusion":[19],"target":[21,102],"out":[22],"of":[23,64,67,114,126,140],"range":[24],"a":[26,32],"few":[27],"frames.":[28],"This":[29],"paper":[30],"proposes":[31],"method":[34,52,121],"based":[35],"on":[36],"multi-cue":[37,127],"integration":[38,49],"auxiliary":[40,58,86,104],"objects":[41,87,105],"deal":[43],"with":[44,92],"these":[45,74],"problems.":[46],"A":[47],"colour-location-prediction":[48],"proposed":[54],"track":[56],"each":[57,68],"object.":[59],"Motivated":[60],"by":[61],"the":[62,97,101,112,115,124,130,138],"idea":[63],"tuning":[65],"weight":[66,125],"cue":[69],"according":[70,80],"their":[72,82],"performances,":[73],"three":[75],"cues":[76],"are":[77],"integrated":[78],"adaptively":[79],"quality":[83],"functions.":[84],"Moreover,":[85],"get":[88],"relative":[90],"information":[91,98,109],"targets":[93,131],"automatically,":[94],"update":[96],"ceaselessly.":[99],"When":[100],"disappears,":[103],"will":[106],"export":[107],"useful":[108],"estimate":[111],"location":[113],"target.":[116],"Experiments":[117],"show":[118],"that":[119],"this":[120],"can":[122],"adapt":[123],"efficiently,":[128],"reinitialize":[129],"after":[132],"long":[133],"time":[134],"disappearance,":[135],"increase":[137],"robustness":[139],"in":[142],"various":[143],"conditions.":[144]},"counts_by_year":[{"year":2013,"cited_by_count":1},{"year":2012,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
