{"id":"https://openalex.org/W2000257956","doi":"https://doi.org/10.1109/icacci.2013.6637451","title":"Efficient silhouette based contour tracking","display_name":"Efficient silhouette based contour tracking","publication_year":2013,"publication_date":"2013-08-01","ids":{"openalex":"https://openalex.org/W2000257956","doi":"https://doi.org/10.1109/icacci.2013.6637451","mag":"2000257956"},"language":"en","primary_location":{"id":"doi:10.1109/icacci.2013.6637451","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icacci.2013.6637451","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 International Conference on Advances in Computing, Communications and Informatics (ICACCI)","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/A5052301812","display_name":"Ajoy Mondal","orcid":"https://orcid.org/0000-0002-4808-8860"},"institutions":[{"id":"https://openalex.org/I6498739","display_name":"Indian Statistical Institute","ror":"https://ror.org/00q2w1j53","country_code":"IN","type":"education","lineage":["https://openalex.org/I6498739"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Ajoy Mondal","raw_affiliation_strings":["Machine Intelligence Unit, Indian Statistical Institute, Kolkata, India","Machine Intell. Unit, Indian Stat. Inst., Kolkata, India"],"affiliations":[{"raw_affiliation_string":"Machine Intelligence Unit, Indian Statistical Institute, Kolkata, India","institution_ids":["https://openalex.org/I6498739"]},{"raw_affiliation_string":"Machine Intell. Unit, Indian Stat. Inst., Kolkata, India","institution_ids":["https://openalex.org/I6498739"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086178863","display_name":"Susmita Ghosh","orcid":"https://orcid.org/0000-0002-1691-761X"},"institutions":[{"id":"https://openalex.org/I170979836","display_name":"Jadavpur University","ror":"https://ror.org/02af4h012","country_code":"IN","type":"education","lineage":["https://openalex.org/I170979836"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Susmita Ghosh","raw_affiliation_strings":["Department of Computer Science & Engineering, Jadavpur University, Kolkata, India","[Department of Computer Science & Engineering, Jadavpur University, Kolkata, India]"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science & Engineering, Jadavpur University, Kolkata, India","institution_ids":["https://openalex.org/I170979836"]},{"raw_affiliation_string":"[Department of Computer Science & Engineering, Jadavpur University, Kolkata, India]","institution_ids":["https://openalex.org/I170979836"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5025656702","display_name":"Ashish Ghosh","orcid":"https://orcid.org/0000-0003-1548-5576"},"institutions":[{"id":"https://openalex.org/I6498739","display_name":"Indian Statistical Institute","ror":"https://ror.org/00q2w1j53","country_code":"IN","type":"education","lineage":["https://openalex.org/I6498739"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Ashish Ghosh","raw_affiliation_strings":["Machine Intelligence Unit, Indian Statistical Institute, Kolkata, India","Machine Intell. Unit, Indian Stat. Inst., Kolkata, India"],"affiliations":[{"raw_affiliation_string":"Machine Intelligence Unit, Indian Statistical Institute, Kolkata, India","institution_ids":["https://openalex.org/I6498739"]},{"raw_affiliation_string":"Machine Intell. Unit, Indian Stat. Inst., Kolkata, India","institution_ids":["https://openalex.org/I6498739"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5052301812"],"corresponding_institution_ids":["https://openalex.org/I6498739"],"apc_list":null,"apc_paid":null,"fwci":0.2722,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.57770181,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":"14","issue":null,"first_page":"1781","last_page":"1786"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":0.9983999729156494,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9983999729156494,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9972000122070312,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9943000078201294,"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/silhouette","display_name":"Silhouette","score":0.9197280406951904},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.8075129985809326},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.7031240463256836},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5698105692863464},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5619924664497375},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5104076266288757},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.4932093024253845},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.4642762541770935},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.4542636275291443},{"id":"https://openalex.org/keywords/boundary","display_name":"Boundary (topology)","score":0.4468890428543091},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.42761728167533875},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.4128923714160919},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.36188918352127075}],"concepts":[{"id":"https://openalex.org/C58103923","wikidata":"https://www.wikidata.org/wiki/Q2286025","display_name":"Silhouette","level":2,"score":0.9197280406951904},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8075129985809326},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7031240463256836},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5698105692863464},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5619924664497375},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5104076266288757},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.4932093024253845},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.4642762541770935},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.4542636275291443},{"id":"https://openalex.org/C62354387","wikidata":"https://www.wikidata.org/wiki/Q875399","display_name":"Boundary (topology)","level":2,"score":0.4468890428543091},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.42761728167533875},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.4128923714160919},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.36188918352127075},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"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":1,"locations":[{"id":"doi:10.1109/icacci.2013.6637451","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icacci.2013.6637451","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 International Conference on Advances in Computing, Communications and Informatics (ICACCI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.7099999785423279}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W972828318","https://openalex.org/W1991113069","https://openalex.org/W1995903777","https://openalex.org/W2040895929","https://openalex.org/W2050022661","https://openalex.org/W2074302875","https://openalex.org/W2082789158","https://openalex.org/W2086921140","https://openalex.org/W2100864581","https://openalex.org/W2104095591","https://openalex.org/W2106649103","https://openalex.org/W2109579504","https://openalex.org/W2131768110","https://openalex.org/W2132515211","https://openalex.org/W2141822239","https://openalex.org/W2145073242","https://openalex.org/W2145803225","https://openalex.org/W2149184914","https://openalex.org/W2150000644","https://openalex.org/W2150785617","https://openalex.org/W2161969291","https://openalex.org/W2162919312","https://openalex.org/W2163532725","https://openalex.org/W2293873019","https://openalex.org/W2525993157","https://openalex.org/W4237938455","https://openalex.org/W6681651645","https://openalex.org/W6727593985"],"related_works":["https://openalex.org/W1622964048","https://openalex.org/W30315714","https://openalex.org/W1906975550","https://openalex.org/W1965274140","https://openalex.org/W779885325","https://openalex.org/W2150972844","https://openalex.org/W2393615320","https://openalex.org/W3110435694","https://openalex.org/W2001760863","https://openalex.org/W2971551846"],"abstract_inverted_index":{"In":[0],"this":[1],"article,":[2],"we":[3],"present":[4],"an":[5],"algorithm":[6],"that":[7],"can":[8],"efficiently":[9],"track":[10],"the":[11,17,44,57,60,65,81,90,94,98,106,111,116,127,134,139,143,158,169,173,177,181,187,193,196,203,208,212,222,231,245,257],"contour":[12,190,199,218,259],"extracted":[13,206],"from":[14,59,93,168],"silhouette":[15,38,156,175,179],"of":[16,20,63,71,101,113,115,138,157,192,202,230,244,256],"moving":[18],"object":[19,58,117,149,153,159,174,178,204,213],"a":[21,40,69,228],"given":[22],"video":[23,240],"sequence":[24],"using":[25],"local":[26],"neighborhood":[27,96],"information":[28],"and":[29,131,150,160,234,264],"fuzzy":[30,48],"k-nearest-neighbor":[31,49],"classifier.":[32],"Object":[33],"is":[34,53,73,86,205,214,248],"represented":[35],"by":[36,250],"its":[37,217],"as":[39,186],"candidate":[41,45,99,224],"model":[42],"in":[43,80,105,142,207,221],"frame.":[46,83,210,225],"A":[47,84],"(fuzzy":[50],"k-NN)":[51],"classifier":[52],"used":[54],"to":[55,75,88,172,180],"distinguish":[56],"background.":[61,151],"Instead":[62],"considering":[64],"whole":[66],"training":[67,91],"set,":[68],"subset":[70,92],"it":[72,236,252],"considered":[74],"classify":[76],"each":[77,102],"unlabeled":[78,103,140],"sample":[79,104],"target":[82,107,144,209,223],"heuristic":[85],"suggested":[87],"generate":[89],"corresponding":[95],"(of":[97],"frame)":[100],"frame,":[108],"depending":[109],"on":[110,237],"amount":[112],"motion":[114],"between":[118],"immediate":[119],"previous":[120],"two":[121,147,238,254],"consecutive":[122],"frames.":[123],"This":[124],"technique":[125],"makes":[126],"classification":[128,135],"process":[129],"faster":[130],"may":[132],"increase":[133],"accuracy.":[136],"Classification":[137],"samples":[141],"frame":[145],"provides":[146],"regions:":[148],"The":[152,242],"region":[154,171,183],"represents":[155],"all":[161],"others":[162],"represent":[163],"non-object":[164,170,182],"region.":[165],"Transition":[166],"pixels":[167,191],"or":[176,189,200,219],"are":[184],"treated":[185],"boundary":[188,197,201,220],"object.":[194],"Connecting":[195],"pixels,":[198],"Hence,":[211],"tracked":[215],"with":[216,253],"We":[226],"show":[227],"realization":[229],"proposed":[232,246],"method":[233,247],"demonstrate":[235],"benchmark":[239],"sequences.":[241],"effectiveness":[243],"established":[249],"comparing":[251],"state":[255],"art":[258],"tracking":[260],"techniques,":[261],"both":[262],"qualitatively":[263],"quantitatively.":[265]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2015,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}