{"id":"https://openalex.org/W2058487881","doi":"https://doi.org/10.1109/icip.2012.6466856","title":"Unsupervised video segmentation by dynamic volume growing and multivariate volume merging using color-texture-gradient features","display_name":"Unsupervised video segmentation by dynamic volume growing and multivariate volume merging using color-texture-gradient features","publication_year":2012,"publication_date":"2012-09-01","ids":{"openalex":"https://openalex.org/W2058487881","doi":"https://doi.org/10.1109/icip.2012.6466856","mag":"2058487881"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2012.6466856","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2012.6466856","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 19th 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/A5049578996","display_name":"Sreenath Rao Vantaram","orcid":null},"institutions":[{"id":"https://openalex.org/I155173764","display_name":"Rochester Institute of Technology","ror":"https://ror.org/00v4yb702","country_code":"US","type":"education","lineage":["https://openalex.org/I155173764"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sreenath Rao Vantaram","raw_affiliation_strings":["Chester F. Carlson Center for Imaging Science, Rochester Institute of Technology, Rochester, NY, USA","Chester F. Carlson Center for Imaging Science, Rochester Institute of Technology, NY, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chester F. Carlson Center for Imaging Science, Rochester Institute of Technology, Rochester, NY, USA","institution_ids":["https://openalex.org/I155173764"]},{"raw_affiliation_string":"Chester F. Carlson Center for Imaging Science, Rochester Institute of Technology, NY, USA","institution_ids":["https://openalex.org/I155173764"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5110980789","display_name":"Eli Saber","orcid":"https://orcid.org/0009-0002-8593-4015"},"institutions":[{"id":"https://openalex.org/I155173764","display_name":"Rochester Institute of Technology","ror":"https://ror.org/00v4yb702","country_code":"US","type":"education","lineage":["https://openalex.org/I155173764"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Eli Saber","raw_affiliation_strings":["Chester F. Carlson Center for Imaging Science, Department of Electrical and Microelectronic Engineering, Rochester Institute of Technology, Rochester, NY, USA","Chester F. Carlson Center for Imaging Science, Rochester Institute of Technology, NY, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chester F. Carlson Center for Imaging Science, Department of Electrical and Microelectronic Engineering, Rochester Institute of Technology, Rochester, NY, USA","institution_ids":["https://openalex.org/I155173764"]},{"raw_affiliation_string":"Chester F. Carlson Center for Imaging Science, Rochester Institute of Technology, NY, USA","institution_ids":["https://openalex.org/I155173764"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.5553,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.69095129,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"5303","issue":null,"first_page":"305","last_page":"308"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9977999925613403,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9977999925613403,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9976000189781189,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9973000288009644,"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/segmentation","display_name":"Segmentation","score":0.6730798482894897},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6707268953323364},{"id":"https://openalex.org/keywords/volume","display_name":"Volume (thermodynamics)","score":0.6088661551475525},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.605043351650238},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5413628816604614},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5338830351829529},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5006959438323975},{"id":"https://openalex.org/keywords/multivariate-statistics","display_name":"Multivariate statistics","score":0.46089521050453186},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.4416516125202179},{"id":"https://openalex.org/keywords/image-texture","display_name":"Image texture","score":0.4276726245880127},{"id":"https://openalex.org/keywords/homogeneous","display_name":"Homogeneous","score":0.4261893630027771},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3001975417137146}],"concepts":[{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6730798482894897},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6707268953323364},{"id":"https://openalex.org/C20556612","wikidata":"https://www.wikidata.org/wiki/Q4469374","display_name":"Volume (thermodynamics)","level":2,"score":0.6088661551475525},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.605043351650238},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5413628816604614},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5338830351829529},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5006959438323975},{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.46089521050453186},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.4416516125202179},{"id":"https://openalex.org/C63099799","wikidata":"https://www.wikidata.org/wiki/Q17147001","display_name":"Image texture","level":4,"score":0.4276726245880127},{"id":"https://openalex.org/C66882249","wikidata":"https://www.wikidata.org/wiki/Q169336","display_name":"Homogeneous","level":2,"score":0.4261893630027771},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3001975417137146},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip.2012.6466856","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2012.6466856","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 19th IEEE International Conference on Image Processing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W1536434015","https://openalex.org/W1975876941","https://openalex.org/W2030346542","https://openalex.org/W2048641376","https://openalex.org/W2084778391","https://openalex.org/W2088169690","https://openalex.org/W2089733759","https://openalex.org/W2121494337","https://openalex.org/W2168507671","https://openalex.org/W2171324559","https://openalex.org/W4255060158","https://openalex.org/W6631986042"],"related_works":["https://openalex.org/W4360784979","https://openalex.org/W3017192027","https://openalex.org/W2204605857","https://openalex.org/W2007664797","https://openalex.org/W2120981610","https://openalex.org/W3129669851","https://openalex.org/W2115198604","https://openalex.org/W2360759360","https://openalex.org/W2799097543","https://openalex.org/W3196005494"],"abstract_inverted_index":{"We":[0],"propose":[1],"a":[2,24,40,62,111],"new":[3],"unsupervised":[4],"technique":[5],"for":[6],"segmentation":[7],"of":[8,49,87],"digital":[9],"video":[10,38,134],"that":[11,45,116],"partitions":[12,91],"its":[13],"constituents":[14],"by":[15,34,95],"identifying":[16],"homogeneous":[17,88],"sub-volumes":[18,118],"within":[19],"the":[20,36,47,53,124],"data":[21],"treated":[22],"as":[23,103,105],"three":[25],"dimensional":[26],"(3-D)":[27],"spatio-temporal":[28,68],"volume.":[29,54],"Our":[30,127],"approach":[31,128],"is":[32,58],"commenced":[33],"subjecting":[35],"input":[37],"to":[39,60,82,122],"3-D":[41],"gradient":[42,57,72,80,108],"detection":[43],"method":[44],"determines":[46],"magnitude":[48],"color":[50,106],"changes":[51],"across":[52],"The":[55],"computed":[56],"utilized":[59],"guide":[61],"volume":[63,113],"growing":[64],"procedure,":[65],"initiated":[66],"at":[67,76],"locations":[69,77],"with":[70,78,98,119,136],"small":[71],"magnitudes":[73],"and":[74,107],"concluded":[75],"large":[79],"magnitudes,":[81],"yield":[83,123],"an":[84,99],"initial":[85],"set":[86],"sub-volumes.":[89],"These":[90],"are":[92],"further":[93],"refined":[94],"integrating":[96],"them":[97],"entropy-based":[100],"texture":[101],"descriptor":[102],"well":[104],"features":[109],"in":[110],"multivariate":[112],"merging":[114],"procedure":[115],"fuses":[117],"similar":[120],"attributes,":[121],"final":[125],"segmentation.":[126],"was":[129],"tested":[130],"on":[131],"several":[132],"simple-to-complex":[133],"sequences":[135],"favorable":[137],"results.":[138]},"counts_by_year":[{"year":2020,"cited_by_count":1},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
