{"id":"https://openalex.org/W2123011731","doi":"https://doi.org/10.1109/avss.2005.1577261","title":"Tracking by cluster analysis of feature points using a mixture particle filter","display_name":"Tracking by cluster analysis of feature points using a mixture particle filter","publication_year":2006,"publication_date":"2006-01-25","ids":{"openalex":"https://openalex.org/W2123011731","doi":"https://doi.org/10.1109/avss.2005.1577261","mag":"2123011731"},"language":"en","primary_location":{"id":"doi:10.1109/avss.2005.1577261","is_oa":false,"landing_page_url":"https://doi.org/10.1109/avss.2005.1577261","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings. IEEE Conference on Advanced Video and Signal Based Surveillance, 2005.","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/A5101492879","display_name":"Wei Du","orcid":"https://orcid.org/0000-0002-3628-3298"},"institutions":[{"id":"https://openalex.org/I157674565","display_name":"University of Li\u00e8ge","ror":"https://ror.org/00afp2z80","country_code":"BE","type":"education","lineage":["https://openalex.org/I157674565"]}],"countries":["BE"],"is_corresponding":true,"raw_author_name":"Wei Du","raw_affiliation_strings":["Department of Electrical Engineering and Computer Science, Institut Montefiore, University of Li\u00e8ge, Liege, Belgium","Dept. of Electr. Eng. & Comput. Sci., Liege Univ., Belgium"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and Computer Science, Institut Montefiore, University of Li\u00e8ge, Liege, Belgium","institution_ids":["https://openalex.org/I157674565"]},{"raw_affiliation_string":"Dept. of Electr. Eng. & Comput. Sci., Liege Univ., Belgium","institution_ids":["https://openalex.org/I157674565"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5024515193","display_name":"Justus Piater","orcid":"https://orcid.org/0000-0002-1898-3362"},"institutions":[{"id":"https://openalex.org/I157674565","display_name":"University of Li\u00e8ge","ror":"https://ror.org/00afp2z80","country_code":"BE","type":"education","lineage":["https://openalex.org/I157674565"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"J. Piater","raw_affiliation_strings":["Department of Electrical Engineering and Computer Science, Institut Montefiore, University of Li\u00e8ge, Liege, Belgium","Dept. of Electr. Eng. & Comput. Sci., Liege Univ., Belgium"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and Computer Science, Institut Montefiore, University of Li\u00e8ge, Liege, Belgium","institution_ids":["https://openalex.org/I157674565"]},{"raw_affiliation_string":"Dept. of Electr. Eng. & Comput. Sci., Liege Univ., Belgium","institution_ids":["https://openalex.org/I157674565"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5101492879"],"corresponding_institution_ids":["https://openalex.org/I157674565"],"apc_list":null,"apc_paid":null,"fwci":8.8389,"has_fulltext":false,"cited_by_count":37,"citation_normalized_percentile":{"value":0.97632719,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"2","issue":null,"first_page":"165","last_page":"170"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.998199999332428,"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":0.9972000122070312,"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/mixture-model","display_name":"Mixture model","score":0.7750239968299866},{"id":"https://openalex.org/keywords/particle-filter","display_name":"Particle filter","score":0.7248091697692871},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6337282061576843},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.6109155416488647},{"id":"https://openalex.org/keywords/cluster","display_name":"Cluster (spacecraft)","score":0.6060547828674316},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5919870138168335},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5206560492515564},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5150191783905029},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.4761262536048889},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4562947750091553},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.4494282603263855},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.44751405715942383},{"id":"https://openalex.org/keywords/disjoint-sets","display_name":"Disjoint sets","score":0.43712693452835083},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.4136471450328827},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.38349631428718567},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3781341016292572},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.15167149901390076},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.0962274968624115},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.08141914010047913}],"concepts":[{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.7750239968299866},{"id":"https://openalex.org/C52421305","wikidata":"https://www.wikidata.org/wiki/Q1151499","display_name":"Particle filter","level":3,"score":0.7248091697692871},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6337282061576843},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.6109155416488647},{"id":"https://openalex.org/C164866538","wikidata":"https://www.wikidata.org/wiki/Q367351","display_name":"Cluster (spacecraft)","level":2,"score":0.6060547828674316},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5919870138168335},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5206560492515564},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5150191783905029},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.4761262536048889},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4562947750091553},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.4494282603263855},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.44751405715942383},{"id":"https://openalex.org/C45340560","wikidata":"https://www.wikidata.org/wiki/Q215382","display_name":"Disjoint sets","level":2,"score":0.43712693452835083},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.4136471450328827},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.38349631428718567},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3781341016292572},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.15167149901390076},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0962274968624115},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.08141914010047913},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","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/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/avss.2005.1577261","is_oa":false,"landing_page_url":"https://doi.org/10.1109/avss.2005.1577261","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings. IEEE Conference on Advanced Video and Signal Based Surveillance, 2005.","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.332.9445","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.332.9445","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.montefiore.ulg.ac.be/~piater/papers/Du-2005-AVSS/","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.412.9379","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.412.9379","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.montefiore.ulg.ac.be/~piater/papers/Du-2005-ICAPR/","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W1606993151","https://openalex.org/W2008466736","https://openalex.org/W2064406221","https://openalex.org/W2107432971","https://openalex.org/W2111308925","https://openalex.org/W2117853077","https://openalex.org/W2118877769","https://openalex.org/W2120911253","https://openalex.org/W2138835141","https://openalex.org/W2146688665","https://openalex.org/W2147953023","https://openalex.org/W2153745896","https://openalex.org/W2160337655","https://openalex.org/W3145294510","https://openalex.org/W6636409418","https://openalex.org/W6677548441"],"related_works":["https://openalex.org/W4256429076","https://openalex.org/W1971174658","https://openalex.org/W2099195351","https://openalex.org/W2348092930","https://openalex.org/W2012063272","https://openalex.org/W3129272755","https://openalex.org/W2138685729","https://openalex.org/W26693340","https://openalex.org/W1963777171","https://openalex.org/W1578916557"],"abstract_inverted_index":{"A":[0],"moving":[1],"target":[2],"produces":[3],"a":[4,71,80,103,148],"coherent":[5],"cluster":[6,72,99],"of":[7,19,67,152,162,169,179],"feature":[8,24,42],"points":[9,43,69],"in":[10,37,70,116],"the":[11,27,32,64,68,74,84,92,117,125,177],"image":[12],"plane.":[13],"This":[14],"motivates":[15],"our":[16,180],"novel":[17],"method":[18,181],"tracking":[20,163],"multiple":[21,78,164],"targets":[22,165],"via":[23],"points.":[25],"First,":[26],"Harris":[28],"corner":[29],"detector":[30],"and":[31,44,54,73,106,121,134,139,167,172],"Lucas-Kanade":[33],"tracker":[34],"are":[35,50,58,119,128,140],"applied":[36],"each":[38],"frame":[39],"to":[40,63,90],"detect":[41],"their":[45,143],"associated":[46],"velocities.":[47],"Points":[48],"that":[49,158],"both":[51],"spatially":[52,136],"co-located":[53],"exhibit":[55],"similar":[56],"motion":[57],"grouped":[59],"into":[60],"clusters.":[61],"Due":[62],"non-Gaussian":[65],"distribution":[66,95],"multi-modality":[75],"resulting":[76],"from":[77],"targets,":[79],"special":[81],"particle":[82,86,112,155],"filter,":[83,87],"mixture":[85,93,104,118,154],"is":[88,100,107,157,160],"adopted":[89],"model":[91],"point":[94],"over":[96],"time.":[97],"Each":[98],"treated":[101],"as":[102],"component":[105,144],"modeled":[108],"by":[109,123,130],"an":[110],"individual":[111],"filter.":[113],"The":[114,150],"filters":[115],"instantiated":[120],"initialized":[122],"applying":[124],"EM":[126],"algorithm,":[127],"reclustered":[129],"merging":[131],"overlapping":[132],"clusters":[133],"splitting":[135],"disjoint":[137],"clusters,":[138],"terminated":[141],"when":[142],"weights":[145],"drop":[146],"below":[147],"threshold.":[149],"advantage":[151],"using":[153],"filtering":[156],"it":[159],"capable":[161],"simultaneously":[166],"also":[168],"handling":[170],"appearing":[171],"disappearing":[173],"targets.":[174],"We":[175],"demonstrate":[176],"effectiveness":[178],"on":[182],"different":[183],"PETS":[184],"datasets.":[185]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2017,"cited_by_count":2},{"year":2015,"cited_by_count":1},{"year":2013,"cited_by_count":2},{"year":2012,"cited_by_count":3}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}
