{"id":"https://openalex.org/W2110456345","doi":"https://doi.org/10.1109/icip.2008.4712071","title":"Multitarget tracking using Gaussian Process Dynamical Model particle filter","display_name":"Multitarget tracking using Gaussian Process Dynamical Model particle filter","publication_year":2008,"publication_date":"2008-01-01","ids":{"openalex":"https://openalex.org/W2110456345","doi":"https://doi.org/10.1109/icip.2008.4712071","mag":"2110456345"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2008.4712071","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2008.4712071","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 15th 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/A5100378385","display_name":"Jing Wang","orcid":"https://orcid.org/0000-0001-8553-7824"},"institutions":[{"id":"https://openalex.org/I108468826","display_name":"Stevens Institute of Technology","ror":"https://ror.org/02z43xh36","country_code":"US","type":"education","lineage":["https://openalex.org/I108468826"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Jing Wang","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Stevens Institute of Technology, Hoboken, NJ, USA","Dept of Electr. & Comput. Eng., Stevens Inst. of Technol., Hoboken, NJ"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Stevens Institute of Technology, Hoboken, NJ, USA","institution_ids":["https://openalex.org/I108468826"]},{"raw_affiliation_string":"Dept of Electr. & Comput. Eng., Stevens Inst. of Technol., Hoboken, NJ","institution_ids":["https://openalex.org/I108468826"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069857153","display_name":"Hong Man","orcid":"https://orcid.org/0000-0002-8892-3066"},"institutions":[{"id":"https://openalex.org/I108468826","display_name":"Stevens Institute of Technology","ror":"https://ror.org/02z43xh36","country_code":"US","type":"education","lineage":["https://openalex.org/I108468826"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hong Man","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Stevens Institute of Technology, Hoboken, NJ, USA","Dept of Electr. & Comput. Eng., Stevens Inst. of Technol., Hoboken, NJ"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Stevens Institute of Technology, Hoboken, NJ, USA","institution_ids":["https://openalex.org/I108468826"]},{"raw_affiliation_string":"Dept of Electr. & Comput. Eng., Stevens Inst. of Technol., Hoboken, NJ","institution_ids":["https://openalex.org/I108468826"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5087888694","display_name":"Yafeng Yin","orcid":"https://orcid.org/0000-0002-9497-6244"},"institutions":[{"id":"https://openalex.org/I108468826","display_name":"Stevens Institute of Technology","ror":"https://ror.org/02z43xh36","country_code":"US","type":"education","lineage":["https://openalex.org/I108468826"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yafeng Yin","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Stevens Institute of Technology, Hoboken, NJ, USA","Dept of Electr. & Comput. Eng., Stevens Inst. of Technol., Hoboken, NJ"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Stevens Institute of Technology, Hoboken, NJ, USA","institution_ids":["https://openalex.org/I108468826"]},{"raw_affiliation_string":"Dept of Electr. & Comput. Eng., Stevens Inst. of Technol., Hoboken, NJ","institution_ids":["https://openalex.org/I108468826"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100378385"],"corresponding_institution_ids":["https://openalex.org/I108468826"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0924792,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"6","issue":null,"first_page":"1580","last_page":"1583"},"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":0.9987000226974487,"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":0.9987000226974487,"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/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9890999794006348,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9848999977111816,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/particle-filter","display_name":"Particle filter","score":0.7845419049263},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.6259692311286926},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5992513298988342},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.585087239742279},{"id":"https://openalex.org/keywords/ensemble-kalman-filter","display_name":"Ensemble Kalman filter","score":0.5266827344894409},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.4932965636253357},{"id":"https://openalex.org/keywords/gaussian-filter","display_name":"Gaussian filter","score":0.4876319468021393},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.48314163088798523},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.4818485975265503},{"id":"https://openalex.org/keywords/state-space-representation","display_name":"State-space representation","score":0.45615851879119873},{"id":"https://openalex.org/keywords/kalman-filter","display_name":"Kalman filter","score":0.45284122228622437},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4347919523715973},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.4266889989376068},{"id":"https://openalex.org/keywords/auxiliary-particle-filter","display_name":"Auxiliary particle filter","score":0.42430973052978516},{"id":"https://openalex.org/keywords/extended-kalman-filter","display_name":"Extended Kalman filter","score":0.34944775700569153},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3364313244819641},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.13041222095489502},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.08400589227676392}],"concepts":[{"id":"https://openalex.org/C52421305","wikidata":"https://www.wikidata.org/wiki/Q1151499","display_name":"Particle filter","level":3,"score":0.7845419049263},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.6259692311286926},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5992513298988342},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.585087239742279},{"id":"https://openalex.org/C79334102","wikidata":"https://www.wikidata.org/wiki/Q3072268","display_name":"Ensemble Kalman filter","level":4,"score":0.5266827344894409},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.4932965636253357},{"id":"https://openalex.org/C65892221","wikidata":"https://www.wikidata.org/wiki/Q1113935","display_name":"Gaussian filter","level":3,"score":0.4876319468021393},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.48314163088798523},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.4818485975265503},{"id":"https://openalex.org/C52918065","wikidata":"https://www.wikidata.org/wiki/Q230945","display_name":"State-space representation","level":2,"score":0.45615851879119873},{"id":"https://openalex.org/C157286648","wikidata":"https://www.wikidata.org/wiki/Q846780","display_name":"Kalman filter","level":2,"score":0.45284122228622437},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4347919523715973},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.4266889989376068},{"id":"https://openalex.org/C52483021","wikidata":"https://www.wikidata.org/wiki/Q4827310","display_name":"Auxiliary particle filter","level":5,"score":0.42430973052978516},{"id":"https://openalex.org/C206833254","wikidata":"https://www.wikidata.org/wiki/Q5421817","display_name":"Extended Kalman filter","level":3,"score":0.34944775700569153},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3364313244819641},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.13041222095489502},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.08400589227676392},{"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/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","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/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"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/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.2008.4712071","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2008.4712071","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 15th 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/W1499578337","https://openalex.org/W2008619276","https://openalex.org/W2110744759","https://openalex.org/W2114879609","https://openalex.org/W2124609748","https://openalex.org/W2136111243","https://openalex.org/W2141251974","https://openalex.org/W2147953023","https://openalex.org/W2166063021","https://openalex.org/W6629966464","https://openalex.org/W6680375596","https://openalex.org/W6682042711"],"related_works":["https://openalex.org/W2368144031","https://openalex.org/W3144709167","https://openalex.org/W2355962871","https://openalex.org/W2127981223","https://openalex.org/W2162253570","https://openalex.org/W2109576686","https://openalex.org/W2593675237","https://openalex.org/W1824810860","https://openalex.org/W2382411933","https://openalex.org/W2070455225"],"abstract_inverted_index":{"We":[0],"present":[1],"a":[2,30,42,47],"particle":[3,27,73,83],"filter":[4,28,84],"based":[5],"multitarget":[6,19],"tracking":[7],"method":[8],"incorporating":[9],"Gaussian":[10,23,67],"process":[11,24,68],"dynamical":[12,25,69],"model":[13,26],"(GPDM)":[14],"to":[15,41,56,88],"improve":[16],"robustness":[17],"in":[18,46,81,92],"tracking.":[20],"With":[21],"the":[22,36,61,72,82,99],"(GPDMPF),":[29],"high-dimensional":[31],"target":[32],"trajectory":[33],"dataset":[34],"of":[35],"observation":[37],"space":[38,45],"is":[39],"projected":[40],"low-dimensional":[43],"latent":[44],"nonlinear":[48],"probabilistic":[49],"manner,":[50],"which":[51],"will":[52],"then":[53],"be":[54],"used":[55,91],"classify":[57],"object":[58],"trajectories,":[59],"predict":[60],"next":[62],"motion":[63],"state,":[64],"and":[65,111,123],"provide":[66],"samples":[70],"for":[71],"filter.":[74],"In":[75,113],"addition,":[76,114],"appearance":[77],"models":[78],"are":[79],"employed":[80],"as":[85],"complimentary":[86],"features":[87],"coordinate":[89],"data":[90],"GPDM.":[93],"The":[94],"simulation":[95],"results":[96],"demonstrate":[97],"that":[98],"approach":[100],"can":[101,116],"track":[102],"more":[103],"than":[104],"four":[105],"targets":[106],"with":[107,119],"reasonable":[108],"runtime":[109],"overhead":[110],"performance.":[112],"it":[115],"successfully":[117],"deal":[118],"occasional":[120],"missing":[121],"frames":[122],"temporary":[124],"occlusions.":[125]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}