{"id":"https://openalex.org/W2765763714","doi":"https://doi.org/10.1109/lsp.2017.2769002","title":"Temporal Signal Basis for Hierarchical Block Motion in Image Sequences","display_name":"Temporal Signal Basis for Hierarchical Block Motion in Image Sequences","publication_year":2017,"publication_date":"2017-11-01","ids":{"openalex":"https://openalex.org/W2765763714","doi":"https://doi.org/10.1109/lsp.2017.2769002","mag":"2765763714"},"language":"en","primary_location":{"id":"doi:10.1109/lsp.2017.2769002","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2017.2769002","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Signal Processing Letters","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/A5101542436","display_name":"Liu Du","orcid":"https://orcid.org/0000-0003-0381-3085"},"institutions":[{"id":"https://openalex.org/I86987016","display_name":"KTH Royal Institute of Technology","ror":"https://ror.org/026vcq606","country_code":"SE","type":"education","lineage":["https://openalex.org/I86987016"]}],"countries":["SE"],"is_corresponding":true,"raw_author_name":"Du Liu","raw_affiliation_strings":["School of Electrical Engineering, KTH Royal Institute of Technology, Stockholm, Sweden"],"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering, KTH Royal Institute of Technology, Stockholm, Sweden","institution_ids":["https://openalex.org/I86987016"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5043892997","display_name":"Markus Flierl","orcid":"https://orcid.org/0000-0002-7807-5681"},"institutions":[{"id":"https://openalex.org/I86987016","display_name":"KTH Royal Institute of Technology","ror":"https://ror.org/026vcq606","country_code":"SE","type":"education","lineage":["https://openalex.org/I86987016"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Markus Flierl","raw_affiliation_strings":["School of Electrical Engineering, KTH Royal Institute of Technology, Stockholm, Sweden"],"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering, KTH Royal Institute of Technology, Stockholm, Sweden","institution_ids":["https://openalex.org/I86987016"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5101542436"],"corresponding_institution_ids":["https://openalex.org/I86987016"],"apc_list":null,"apc_paid":null,"fwci":0.182,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.57710393,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"25","issue":"1","first_page":"10","last_page":"14"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9987000226974487,"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":0.9987000226974487,"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":0.9970999956130981,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9958999752998352,"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":0.6384938955307007},{"id":"https://openalex.org/keywords/basis","display_name":"Basis (linear algebra)","score":0.6358456015586853},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5627993941307068},{"id":"https://openalex.org/keywords/motion-estimation","display_name":"Motion estimation","score":0.5178347229957581},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.5157259106636047},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.509779155254364},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.44272732734680176},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.440543532371521},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.42526257038116455},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.403897225856781},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.25916773080825806}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6384938955307007},{"id":"https://openalex.org/C12426560","wikidata":"https://www.wikidata.org/wiki/Q189569","display_name":"Basis (linear algebra)","level":2,"score":0.6358456015586853},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5627993941307068},{"id":"https://openalex.org/C10161872","wikidata":"https://www.wikidata.org/wiki/Q557891","display_name":"Motion estimation","level":2,"score":0.5178347229957581},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.5157259106636047},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.509779155254364},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.44272732734680176},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.440543532371521},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.42526257038116455},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.403897225856781},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.25916773080825806},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lsp.2017.2769002","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2017.2769002","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Signal Processing Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7","score":0.8500000238418579}],"awards":[{"id":"https://openalex.org/G6500318153","display_name":null,"funder_award_id":"2011-5841","funder_id":"https://openalex.org/F4320321033","funder_display_name":"Svenska Forskningsr\u00e5det Formas"}],"funders":[{"id":"https://openalex.org/F4320321033","display_name":"Svenska Forskningsr\u00e5det Formas","ror":"https://ror.org/03pjs1y45"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W610997267","https://openalex.org/W1916685473","https://openalex.org/W1965106955","https://openalex.org/W1975994995","https://openalex.org/W1991252559","https://openalex.org/W2008878870","https://openalex.org/W2010650451","https://openalex.org/W2026977805","https://openalex.org/W2050048686","https://openalex.org/W2050320982","https://openalex.org/W2086749127","https://openalex.org/W2101491865","https://openalex.org/W2120485259","https://openalex.org/W2123886129","https://openalex.org/W2132555912","https://openalex.org/W2136122855","https://openalex.org/W2148377450","https://openalex.org/W2151128232","https://openalex.org/W2158787690","https://openalex.org/W2160050411","https://openalex.org/W2167200240","https://openalex.org/W2557464755","https://openalex.org/W2959406683","https://openalex.org/W3103475671","https://openalex.org/W4238253035","https://openalex.org/W4388323202","https://openalex.org/W6682227116","https://openalex.org/W6689213722"],"related_works":["https://openalex.org/W2392320810","https://openalex.org/W2078609410","https://openalex.org/W2372403409","https://openalex.org/W2387724274","https://openalex.org/W4382011329","https://openalex.org/W4242726756","https://openalex.org/W1983265578","https://openalex.org/W2534768866","https://openalex.org/W2001234467","https://openalex.org/W1563772308"],"abstract_inverted_index":{"In":[0,21,38],"classic":[1],"data":[2],"compression,":[3],"the":[4,11,15,18,25,29,36,72,77,85,93,95,98,102,131,136,141,144,151,155,160,165,168,174,182],"optimal":[5],"transform":[6,13],"for":[7,63,190],"energy":[8],"compaction":[9],"is":[10,69,79,89,105,133,188],"Karhunen-L\u00f2eve":[12],"with":[14],"eigenvectors":[16,30],"of":[17,167,173,184],"covariance":[19,26,44,66,87,99,120,169,186],"matrix.":[20],"coding":[22,161],"applications,":[23],"neither":[24],"matrix":[27,45,62,67,88,100,104,146],"nor":[28],"can":[31,122],"be":[32,123],"easily":[33],"transmitted":[34],"to":[35,92,164,171],"decoder.":[37],"this":[39],"letter,":[40],"we":[41,116,158],"introduce":[42],"a":[43,126],"model":[46,68,121,129,170,187],"based":[47],"on":[48],"graphs":[49],"determined":[50,80],"by":[51,81,135],"hierarchical":[52],"block":[53,82,192],"motion":[54,193],"in":[55,143,150,194],"image":[56,195],"sequences":[57],"and":[58,101,107,140],"use":[59],"its":[60],"eigenvector":[61,109],"compression.":[64],"The":[65,177],"defined":[70],"using":[71],"graph":[73,78],"distance":[74],"matrix,":[75],"where":[76,130],"motion.":[83],"As":[84],"proposed":[86],"closely":[90],"related":[91],"graph,":[94],"relation":[96],"between":[97],"Laplacian":[103,175],"studied":[106],"their":[108],"matrices":[110],"are":[111],"discussed.":[112],"From":[113],"our":[114,119,185],"assumptions,":[115],"show":[117,180],"that":[118,172,181],"viewed":[124],"as":[125],"Gaussian":[127],"graphical":[128],"signal":[132],"described":[134],"second":[137],"order":[138],"statistics":[139],"zeros":[142],"precision":[145],"indicate":[147],"missing":[148],"edges":[149],"graph.":[152],"To":[153],"assess":[154],"compression":[156],"performance,":[157],"relate":[159],"gain":[162],"due":[163],"eigenbasis":[166,183],"eigenbasis.":[176],"experimental":[178],"results":[179],"advantageous":[189],"tree-structured":[191],"sequences.":[196]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2018,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}