{"id":"https://openalex.org/W1924053412","doi":"https://doi.org/10.5220/0004731006050612","title":"Improving Visual Tracking Robustness in Cluttered and Occluded Environments using Particle Filter with Hybrid Resampling","display_name":"Improving Visual Tracking Robustness in Cluttered and Occluded Environments using Particle Filter with Hybrid Resampling","publication_year":2014,"publication_date":"2014-01-01","ids":{"openalex":"https://openalex.org/W1924053412","doi":"https://doi.org/10.5220/0004731006050612","mag":"1924053412"},"language":"en","primary_location":{"id":"doi:10.5220/0004731006050612","is_oa":true,"landing_page_url":"https://doi.org/10.5220/0004731006050612","pdf_url":null,"source":null,"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 9th International Conference on Computer Vision Theory and Applications","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.5220/0004731006050612","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5078484174","display_name":"Fl\u00e1vio de Barros Vidal","orcid":"https://orcid.org/0000-0002-6317-218X"},"institutions":[{"id":"https://openalex.org/I150729083","display_name":"Universidade de Bras\u00edlia","ror":"https://ror.org/02xfp8v59","country_code":"BR","type":"education","lineage":["https://openalex.org/I150729083"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Flavio de Barros Vidal","raw_affiliation_strings":["Department of Computer Science, University of Brasilia, Distrito Federal, 70.910-900, Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Brasilia, Distrito Federal, 70.910-900, Brazil","institution_ids":["https://openalex.org/I150729083"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073234232","display_name":"Alexandre Zaghetto","orcid":null},"institutions":[{"id":"https://openalex.org/I150729083","display_name":"Universidade de Bras\u00edlia","ror":"https://ror.org/02xfp8v59","country_code":"BR","type":"education","lineage":["https://openalex.org/I150729083"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Alexandre Zaghetto","raw_affiliation_strings":["Department of Computer Science, University of Brasilia, Distrito Federal, 70.910-900, Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Brasilia, Distrito Federal, 70.910-900, Brazil","institution_ids":["https://openalex.org/I150729083"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082263948","display_name":"Diego A. L. Cordoba","orcid":null},"institutions":[{"id":"https://openalex.org/I150729083","display_name":"Universidade de Bras\u00edlia","ror":"https://ror.org/02xfp8v59","country_code":"BR","type":"education","lineage":["https://openalex.org/I150729083"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Diego A. L. Cordoba","raw_affiliation_strings":["Department of Computer Science, University of Brasilia, Distrito Federal, 70.910-900, Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Brasilia, Distrito Federal, 70.910-900, Brazil","institution_ids":["https://openalex.org/I150729083"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5036338172","display_name":"Carla M. C. C. Koike","orcid":null},"institutions":[{"id":"https://openalex.org/I150729083","display_name":"Universidade de Bras\u00edlia","ror":"https://ror.org/02xfp8v59","country_code":"BR","type":"education","lineage":["https://openalex.org/I150729083"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Carla M. C. C. Koike","raw_affiliation_strings":["Department of Computer Science, University of Brasilia, Distrito Federal, 70.910-900, Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Brasilia, Distrito Federal, 70.910-900, Brazil","institution_ids":["https://openalex.org/I150729083"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I150729083"],"apc_list":null,"apc_paid":null,"fwci":0.3596,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.54763767,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"605","last_page":"612"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9995999932289124,"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":0.9995999932289124,"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":0.9805999994277954,"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"}},{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9702000021934509,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/resampling","display_name":"Resampling","score":0.8672330975532532},{"id":"https://openalex.org/keywords/particle-filter","display_name":"Particle filter","score":0.8520797491073608},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.8436601161956787},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7738350033760071},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.7696592807769775},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6636133790016174},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5885058045387268},{"id":"https://openalex.org/keywords/eye-tracking","display_name":"Eye tracking","score":0.5748658776283264},{"id":"https://openalex.org/keywords/video-tracking","display_name":"Video tracking","score":0.5096850395202637},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.504280686378479},{"id":"https://openalex.org/keywords/auxiliary-particle-filter","display_name":"Auxiliary particle filter","score":0.4590100646018982},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.41177576780319214},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.34835541248321533},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.2941587567329407},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.20780566334724426},{"id":"https://openalex.org/keywords/kalman-filter","display_name":"Kalman filter","score":0.20747381448745728},{"id":"https://openalex.org/keywords/ensemble-kalman-filter","display_name":"Ensemble Kalman filter","score":0.0884125828742981}],"concepts":[{"id":"https://openalex.org/C150921843","wikidata":"https://www.wikidata.org/wiki/Q1170431","display_name":"Resampling","level":2,"score":0.8672330975532532},{"id":"https://openalex.org/C52421305","wikidata":"https://www.wikidata.org/wiki/Q1151499","display_name":"Particle filter","level":3,"score":0.8520797491073608},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.8436601161956787},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7738350033760071},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7696592807769775},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6636133790016174},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5885058045387268},{"id":"https://openalex.org/C56461940","wikidata":"https://www.wikidata.org/wiki/Q970687","display_name":"Eye tracking","level":2,"score":0.5748658776283264},{"id":"https://openalex.org/C202474056","wikidata":"https://www.wikidata.org/wiki/Q1931635","display_name":"Video tracking","level":3,"score":0.5096850395202637},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.504280686378479},{"id":"https://openalex.org/C52483021","wikidata":"https://www.wikidata.org/wiki/Q4827310","display_name":"Auxiliary particle filter","level":5,"score":0.4590100646018982},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.41177576780319214},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.34835541248321533},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.2941587567329407},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.20780566334724426},{"id":"https://openalex.org/C157286648","wikidata":"https://www.wikidata.org/wiki/Q846780","display_name":"Kalman filter","level":2,"score":0.20747381448745728},{"id":"https://openalex.org/C79334102","wikidata":"https://www.wikidata.org/wiki/Q3072268","display_name":"Ensemble Kalman filter","level":4,"score":0.0884125828742981},{"id":"https://openalex.org/C19417346","wikidata":"https://www.wikidata.org/wiki/Q7922","display_name":"Pedagogy","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C206833254","wikidata":"https://www.wikidata.org/wiki/Q5421817","display_name":"Extended Kalman filter","level":3,"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/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"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/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.5220/0004731006050612","is_oa":true,"landing_page_url":"https://doi.org/10.5220/0004731006050612","pdf_url":null,"source":null,"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 9th International Conference on Computer Vision Theory and Applications","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.5220/0004731006050612","is_oa":true,"landing_page_url":"https://doi.org/10.5220/0004731006050612","pdf_url":null,"source":null,"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 9th International Conference on Computer Vision Theory and Applications","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W3144709167","https://openalex.org/W1824810860","https://openalex.org/W2162253570","https://openalex.org/W2368144031","https://openalex.org/W2355962871","https://openalex.org/W2758742130","https://openalex.org/W2126226614","https://openalex.org/W2406829934","https://openalex.org/W2862160893","https://openalex.org/W2376126247"],"abstract_inverted_index":{"Occlusions":[0],"and":[1,52,56,74],"cluttered":[2,92],"environments":[3],"represent":[4],"real":[5],"challenges":[6],"for":[7,16,26],"visual":[8,27],"tracking":[9,28,81],"methods.":[10],"In":[11],"order":[12],"to":[13,44],"increase":[14],"robustness":[15],"such":[17],"situations,":[18],"we":[19],"present,":[20],"in":[21,61,91,97],"this":[22],"article,":[23],"a":[24,30,41,71],"method":[25,67],"using":[29,40,70],"Particle":[31],"Filter":[32],"with":[33,79,99],"Hybrid":[34],"Resampling.":[35],"Our":[36],"approach":[37,88],"consists":[38],"of":[39,48],"particle":[42],"filter":[43],"estimate":[45],"the":[46,49,62,75],"state":[47],"tracked":[50],"object,":[51],"both":[53],"particles'":[54],"inertia":[55],"update":[57],"information":[58],"are":[59,77],"used":[60],"resampling":[63],"stage.":[64],"The":[65,83],"proposed":[66],"is":[68],"tested":[69],"public":[72],"benchmark":[73],"results":[76,84],"compared":[78],"other":[80],"algorithms.":[82],"show":[85],"that":[86],"our":[87],"performs":[89],"better":[90],"environments,":[93],"as":[94,96],"well":[95],"situations":[98],"total":[100],"or":[101],"partial":[102],"occlusions.":[103]},"counts_by_year":[{"year":2017,"cited_by_count":1},{"year":2015,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2016-06-24T00:00:00"}
