{"id":"https://openalex.org/W2971317691","doi":"https://doi.org/10.1109/icip.2019.8803024","title":"Graph Based Non-Uniform Sampling and Reconstruction of Depth Maps","display_name":"Graph Based Non-Uniform Sampling and Reconstruction of Depth Maps","publication_year":2019,"publication_date":"2019-08-26","ids":{"openalex":"https://openalex.org/W2971317691","doi":"https://doi.org/10.1109/icip.2019.8803024","mag":"2971317691"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2019.8803024","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2019.8803024","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://infoscience.epfl.ch/handle/20.500.14299/159670","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5063288559","display_name":"Jingyu Yang","orcid":"https://orcid.org/0000-0002-7521-7920"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingyu Yang","raw_affiliation_strings":["Tianjin University, Tianjin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100407910","display_name":"Wenqiang Xu","orcid":"https://orcid.org/0000-0002-8648-5576"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenqiang Xu","raw_affiliation_strings":["Tianjin University, Tianjin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055580414","display_name":"Xinchen Ye","orcid":"https://orcid.org/0000-0001-5328-3911"},"institutions":[{"id":"https://openalex.org/I27357992","display_name":"Dalian University of Technology","ror":"https://ror.org/023hj5876","country_code":"CN","type":"education","lineage":["https://openalex.org/I27357992"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinchen Ye","raw_affiliation_strings":["Dalian University of Technology, Dalian, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dalian University of Technology, Dalian, China","institution_ids":["https://openalex.org/I27357992"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000947076","display_name":"Pascal Frossard","orcid":"https://orcid.org/0000-0002-4010-714X"},"institutions":[{"id":"https://openalex.org/I5124864","display_name":"\u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne","ror":"https://ror.org/02s376052","country_code":"CH","type":"education","lineage":["https://openalex.org/I2799323385","https://openalex.org/I5124864"]}],"countries":["CH"],"is_corresponding":false,"raw_author_name":"Pascal Frossard","raw_affiliation_strings":["Ecole Polytechnique F\u00e9d\u00e9rale de Lausanne, Lausanne, Switzerland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ecole Polytechnique F\u00e9d\u00e9rale de Lausanne, Lausanne, Switzerland","institution_ids":["https://openalex.org/I5124864"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5112943768","display_name":"Kun Li","orcid":"https://orcid.org/0000-0003-4845-8005"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kun Li","raw_affiliation_strings":["Tianjin University, Tianjin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2324","last_page":"2328"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12153","display_name":"Advanced Optical Sensing Technologies","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/3105","display_name":"Instrumentation"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12153","display_name":"Advanced Optical Sensing Technologies","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/3105","display_name":"Instrumentation"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":0.9976999759674072,"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/T11019","display_name":"Image Enhancement Techniques","score":0.9933000206947327,"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/sampling","display_name":"Sampling (signal processing)","score":0.6392380595207214},{"id":"https://openalex.org/keywords/classification-of-discontinuities","display_name":"Classification of discontinuities","score":0.6201366782188416},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5858978033065796},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5804479718208313},{"id":"https://openalex.org/keywords/cut","display_name":"Cut","score":0.5477920174598694},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.534596860408783},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.48039868474006653},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.47647783160209656},{"id":"https://openalex.org/keywords/image-resolution","display_name":"Image resolution","score":0.47494032979011536},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4725225567817688},{"id":"https://openalex.org/keywords/iterative-reconstruction","display_name":"Iterative reconstruction","score":0.4580037593841553},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2979486882686615},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.2913973927497864},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.1889742612838745},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.18583464622497559},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.16059395670890808}],"concepts":[{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.6392380595207214},{"id":"https://openalex.org/C15627037","wikidata":"https://www.wikidata.org/wiki/Q541961","display_name":"Classification of discontinuities","level":2,"score":0.6201366782188416},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5858978033065796},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5804479718208313},{"id":"https://openalex.org/C5134670","wikidata":"https://www.wikidata.org/wiki/Q1626444","display_name":"Cut","level":4,"score":0.5477920174598694},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.534596860408783},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.48039868474006653},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.47647783160209656},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.47494032979011536},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4725225567817688},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.4580037593841553},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2979486882686615},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.2913973927497864},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.1889742612838745},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.18583464622497559},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.16059395670890808},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icip.2019.8803024","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2019.8803024","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"},{"id":"pmh:oai:infoscience.epfl.ch:268757","is_oa":true,"landing_page_url":"https://infoscience.epfl.ch/handle/20.500.14299/159670","pdf_url":null,"source":{"id":"https://openalex.org/S4306400487","display_name":"Infoscience (Ecole Polytechnique F\u00e9d\u00e9rale de Lausanne)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"conference proceedings"}],"best_oa_location":{"id":"pmh:oai:infoscience.epfl.ch:268757","is_oa":true,"landing_page_url":"https://infoscience.epfl.ch/handle/20.500.14299/159670","pdf_url":null,"source":{"id":"https://openalex.org/S4306400487","display_name":"Infoscience (Ecole Polytechnique F\u00e9d\u00e9rale de Lausanne)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"conference proceedings"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","score":0.6700000166893005,"display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1669104078","https://openalex.org/W1994184495","https://openalex.org/W2005441409","https://openalex.org/W2016926874","https://openalex.org/W2060626235","https://openalex.org/W2099712288","https://openalex.org/W2101491865","https://openalex.org/W2104600947","https://openalex.org/W2124202434","https://openalex.org/W2125188192","https://openalex.org/W2155479981","https://openalex.org/W2518792500","https://openalex.org/W2521490062","https://openalex.org/W2591997370","https://openalex.org/W2790567986","https://openalex.org/W2800540452","https://openalex.org/W6678681887","https://openalex.org/W6750955416"],"related_works":["https://openalex.org/W1972096828","https://openalex.org/W2529137940","https://openalex.org/W2044092692","https://openalex.org/W2614621130","https://openalex.org/W2547665164","https://openalex.org/W3103111272","https://openalex.org/W4289655544","https://openalex.org/W2375137989","https://openalex.org/W2010171670","https://openalex.org/W2537408670"],"abstract_inverted_index":{"High-quality":[0],"depth":[1,20,45,64,69,78,100,134,151,187],"sensing":[2],"is":[3,32,142],"highly":[4],"demanded":[5],"in":[6,115,126],"intelligent":[7],"computer":[8],"vision,":[9],"3DTV,":[10],"and":[11,66,80,123,152,182],"many":[12],"other":[13],"related":[14],"fields.":[15],"However,":[16],"prevalent":[17],"time-of-fly":[18],"(ToF)":[19],"sensors":[21],"are":[22,83,102],"of":[23,29,44,50,63,108,171],"low":[24],"resolution":[25,52],"as":[26,121],"the":[27,35,41,60,67,106,150,157,167,178],"number":[28],"pixel-level":[30],"demodulators":[31],"limited.":[33],"Moreover,":[34],"rectangular":[36,55],"sampling":[37,62,79,96,117,181],"does":[38],"not":[39],"consider":[40],"signal":[42,88],"characteristics":[43],"maps.":[46],"Being":[47],"a":[48,93,109,132,138],"departure":[49],"previous":[51],"enhancement":[53],"on":[54,86,105,166],"sampling,":[56],"this":[57],"paper":[58],"investigates":[59],"non-uniform":[61,95,180],"maps,":[65],"high-resolution":[68],"reconstruction":[70,81,135,158,183],"from":[71],"limited":[72],"non-uniformly":[73],"distributed":[74],"samples.":[75],"The":[76],"proposed":[77],"schemes":[82],"developed":[84],"based":[85,104,165],"graph":[87,111,139],"processing.":[89],"We":[90,129],"first":[91],"propose":[92,131],"graph-based":[94,133],"(GNS)":[97],"scheme,":[98],"where":[99],"signals":[101],"sampled":[103],"response":[107],"high-pass":[110],"filter,":[112],"which":[113],"results":[114,175],"denser":[116],"around":[118],"discontinuities":[119],"such":[120],"edges":[122],"contours":[124],"than":[125],"smooth":[127],"regions.":[128],"then":[130],"(GDR)":[136],"framework,where":[137],"Laplacian":[140],"regularizer":[141],"designed":[143],"to":[144],"fully":[145],"exploit":[146],"structural":[147],"correlation":[148],"between":[149],"photometric":[153],"images.":[154],"To":[155],"solve":[156],"problem,":[159],"we":[160],"derive":[161],"an":[162],"efficient":[163],"algorithm":[164],"alternating":[168],"direction":[169],"method":[170,184],"multipliers":[172],"(ADMM).":[173],"Experimental":[174],"show":[176],"that":[177],"GNS-GDR":[179],"achieves":[185],"high-quality":[186],"sensing,":[188],"outperforming":[189],"several":[190],"state-of-the-art":[191],"schemes.":[192]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}