{"id":"https://openalex.org/W2579037638","doi":"https://doi.org/10.2352/issn.2470-1173.2016.15.ipas-187","title":"Video segmentation in presence of static and dynamic textures","display_name":"Video segmentation in presence of static and dynamic textures","publication_year":2016,"publication_date":"2016-02-14","ids":{"openalex":"https://openalex.org/W2579037638","doi":"https://doi.org/10.2352/issn.2470-1173.2016.15.ipas-187","mag":"2579037638"},"language":"en","primary_location":{"id":"doi:10.2352/issn.2470-1173.2016.15.ipas-187","is_oa":false,"landing_page_url":"https://doi.org/10.2352/issn.2470-1173.2016.15.ipas-187","pdf_url":null,"source":{"id":"https://openalex.org/S4210227276","display_name":"Electronic Imaging","issn_l":"2470-1173","issn":["2470-1173"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Electronic Imaging","raw_type":"journal-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/A5016907914","display_name":"V. A. Frantc","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Frantc V A","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026430708","display_name":"Sergey Makov","orcid":"https://orcid.org/0000-0001-7317-6216"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Makov S V","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076403380","display_name":"Viacheslav Voronin","orcid":"https://orcid.org/0000-0001-8114-6383"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Voronin V V","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102981113","display_name":"\u0412. \u0418. \u041c\u0430\u0440\u0447\u0443\u043a","orcid":"https://orcid.org/0000-0001-8576-0081"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Marchuk V I","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100535546","display_name":"Stradanchenko S. G","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Stradanchenko S. G","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5090213299","display_name":"Karen Egiazarian","orcid":"https://orcid.org/0000-0002-8135-1085"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Egiazarian K O","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.3315,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.68519961,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"28","issue":"15","first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9969000220298767,"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":0.9969000220298767,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.996399998664856,"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":0.9950000047683716,"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/computer-science","display_name":"Computer science","score":0.7813014984130859},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7790971994400024},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6721665263175964},{"id":"https://openalex.org/keywords/markov-random-field","display_name":"Markov random field","score":0.6050661206245422},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5805369019508362},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5254302024841309},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4893636107444763},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4339081645011902},{"id":"https://openalex.org/keywords/image-texture","display_name":"Image texture","score":0.41570404171943665}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7813014984130859},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7790971994400024},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6721665263175964},{"id":"https://openalex.org/C2778045648","wikidata":"https://www.wikidata.org/wiki/Q176827","display_name":"Markov random field","level":4,"score":0.6050661206245422},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5805369019508362},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5254302024841309},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4893636107444763},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4339081645011902},{"id":"https://openalex.org/C63099799","wikidata":"https://www.wikidata.org/wiki/Q17147001","display_name":"Image texture","level":4,"score":0.41570404171943665}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.2352/issn.2470-1173.2016.15.ipas-187","is_oa":false,"landing_page_url":"https://doi.org/10.2352/issn.2470-1173.2016.15.ipas-187","pdf_url":null,"source":{"id":"https://openalex.org/S4210227276","display_name":"Electronic Imaging","issn_l":"2470-1173","issn":["2470-1173"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Electronic Imaging","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy","score":0.6299999952316284}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4233585817","https://openalex.org/W4360784979","https://openalex.org/W3017192027","https://openalex.org/W1522196789","https://openalex.org/W2373481280","https://openalex.org/W2204605857","https://openalex.org/W2016045932","https://openalex.org/W1675950995","https://openalex.org/W1996489018","https://openalex.org/W2007664797"],"abstract_inverted_index":{"This":[0],"paper":[1],"describes":[2],"an":[3],"approach":[4,131,147],"to":[5,12,17,134],"video":[6,15,55,62,150],"sequence":[7],"over–segmentation.":[8],"The":[9,96],"objective":[10],"is":[11,46,132],"split":[13],"the":[14,28,66],"up":[16],"set":[18],"of":[19,35,51,83,86,99,115,124,153],"disjoint":[20],"spatio–temporal":[21],"regions":[22],"with":[23,118],"homogeneous":[24],"texture":[25,40],"properties.":[26],"In":[27],"work":[29],"we":[30,110],"consider":[31],"three":[32],"possible":[33],"types":[34],"regions:":[36],"static":[37,92,136,154],"texture,":[38],"dynamic":[39,94,138,156],"and":[41,60,93,122,137,155,158],"non-textured":[42],"region.":[43],"Video":[44],"over-segmentation":[45,109],"useful":[47],"for":[48],"wide":[49],"range":[50],"applications,":[52],"including":[53],"perceptual":[54],"coding,":[56],"video-based":[57],"object":[58],"recognition":[59],"high-level":[61],"segmentation.":[63],"We":[64,127,143],"treat":[65],"problem":[67,71],"as":[68],"a":[69,73],"labeling":[70],"on":[72,91,148],"Markov":[74],"Random":[75],"Field.":[76],"Observed":[77],"data":[78],"are":[79],"represented":[80],"by":[81],"output":[82],"fully-connected":[84],"layer":[85],"convolutional":[87],"neural":[88],"network":[89],"trained":[90],"textures.":[95],"hidden":[97],"states":[98],"our":[100,130,146],"model":[101],"represent":[102],"appropriate":[103],"region":[104],"labels.":[105],"To":[106],"provide":[107],"robust":[108],"employ":[111],"energy":[112],"function":[113],"composed":[114],"terms":[116],"associated":[117],"neighboring":[119],"voxels":[120],"similarity":[121],"smoothness":[123],"obtained":[125],"supervoxels.":[126],"show":[128],"that":[129],"able":[133],"segment":[135],"textures":[139,157],"in":[140],"simultaneous":[141],"fashion.":[142],"have":[144],"tested":[145],"several":[149],"sequences":[151],"rich":[152],"it":[159],"has":[160],"shown":[161],"promising":[162],"results.":[163]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1}],"updated_date":"2026-06-24T06:17:17.354583","created_date":"2025-10-10T00:00:00"}