{"id":"https://openalex.org/W4312412004","doi":"https://doi.org/10.1109/iros47612.2022.9981549","title":"Audio-Visual Depth and Material Estimation for Robot Navigation","display_name":"Audio-Visual Depth and Material Estimation for Robot Navigation","publication_year":2022,"publication_date":"2022-10-23","ids":{"openalex":"https://openalex.org/W4312412004","doi":"https://doi.org/10.1109/iros47612.2022.9981549"},"language":"en","primary_location":{"id":"doi:10.1109/iros47612.2022.9981549","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros47612.2022.9981549","pdf_url":null,"source":{"id":"https://openalex.org/S4363607704","display_name":"2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5102778571","display_name":"Justin Wilson","orcid":"https://orcid.org/0000-0003-2768-3799"},"institutions":[{"id":"https://openalex.org/I114027177","display_name":"University of North Carolina at Chapel Hill","ror":"https://ror.org/0130frc33","country_code":"US","type":"education","lineage":["https://openalex.org/I114027177"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Justin Wilson","raw_affiliation_strings":["University of North Carolina at Chapel Hill,Department of Computer Science,United States","Department of Computer Science, University of North Carolina at Chapel Hill, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of North Carolina at Chapel Hill,Department of Computer Science,United States","institution_ids":["https://openalex.org/I114027177"]},{"raw_affiliation_string":"Department of Computer Science, University of North Carolina at Chapel Hill, United States","institution_ids":["https://openalex.org/I114027177"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011535172","display_name":"Nicholas Rewkowski","orcid":null},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nicholas Rewkowski","raw_affiliation_strings":["University of Maryland at College Park,Department of Computer Science,United States","Department of Computer Science, University of Maryland at College Park, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Maryland at College Park,Department of Computer Science,United States","institution_ids":["https://openalex.org/I66946132"]},{"raw_affiliation_string":"Department of Computer Science, University of Maryland at College Park, United States","institution_ids":["https://openalex.org/I66946132"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102878981","display_name":"Ming C. Lin","orcid":"https://orcid.org/0000-0003-3736-6949"},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ming C. Lin","raw_affiliation_strings":["University of Maryland at College Park,Department of Computer Science,United States","Department of Computer Science, University of Maryland at College Park, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Maryland at College Park,Department of Computer Science,United States","institution_ids":["https://openalex.org/I66946132"]},{"raw_affiliation_string":"Department of Computer Science, University of Maryland at College Park, United States","institution_ids":["https://openalex.org/I66946132"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.5537,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.63443818,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"9239","last_page":"9246"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11309","display_name":"Music and Audio Processing","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T11309","display_name":"Music and Audio Processing","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T10860","display_name":"Speech and Audio Processing","score":0.996999979019165,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T11439","display_name":"Video Analysis and Summarization","score":0.991599977016449,"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-vision","display_name":"Computer vision","score":0.7565650343894958},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7560373544692993},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7094985842704773},{"id":"https://openalex.org/keywords/inpainting","display_name":"Inpainting","score":0.48335474729537964},{"id":"https://openalex.org/keywords/depth-map","display_name":"Depth map","score":0.4664532542228699},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.45159316062927246},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.16952762007713318}],"concepts":[{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7565650343894958},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7560373544692993},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7094985842704773},{"id":"https://openalex.org/C11727466","wikidata":"https://www.wikidata.org/wiki/Q1628157","display_name":"Inpainting","level":3,"score":0.48335474729537964},{"id":"https://openalex.org/C141268832","wikidata":"https://www.wikidata.org/wiki/Q2940499","display_name":"Depth map","level":3,"score":0.4664532542228699},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.45159316062927246},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.16952762007713318}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iros47612.2022.9981549","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros47612.2022.9981549","pdf_url":null,"source":{"id":"https://openalex.org/S4363607704","display_name":"2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","score":0.4099999964237213,"display_name":"Sustainable cities and communities"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320338281","display_name":"Army Research Office","ror":"https://ror.org/05epdh915"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":82,"referenced_works":["https://openalex.org/W114517082","https://openalex.org/W1522301498","https://openalex.org/W1686810756","https://openalex.org/W1918869474","https://openalex.org/W1920022804","https://openalex.org/W1993716293","https://openalex.org/W1994281102","https://openalex.org/W1996160964","https://openalex.org/W2025572378","https://openalex.org/W2038484192","https://openalex.org/W2044576428","https://openalex.org/W2052666245","https://openalex.org/W2099332139","https://openalex.org/W2118774185","https://openalex.org/W2122111042","https://openalex.org/W2125188427","https://openalex.org/W2135029798","https://openalex.org/W2143802570","https://openalex.org/W2151819132","https://openalex.org/W2153811331","https://openalex.org/W2170435459","https://openalex.org/W2331393093","https://openalex.org/W2412393473","https://openalex.org/W2478051194","https://openalex.org/W2502505937","https://openalex.org/W2511428026","https://openalex.org/W2547141619","https://openalex.org/W2550143307","https://openalex.org/W2557465155","https://openalex.org/W2565233142","https://openalex.org/W2586821239","https://openalex.org/W2593116425","https://openalex.org/W2594519801","https://openalex.org/W2641889749","https://openalex.org/W2727600720","https://openalex.org/W2764198839","https://openalex.org/W2770709216","https://openalex.org/W2780568882","https://openalex.org/W2806568678","https://openalex.org/W2811180360","https://openalex.org/W2838290523","https://openalex.org/W2895085622","https://openalex.org/W2949830259","https://openalex.org/W2963150162","https://openalex.org/W2963502419","https://openalex.org/W2968826970","https://openalex.org/W2970786321","https://openalex.org/W2972607952","https://openalex.org/W2979485309","https://openalex.org/W2981985754","https://openalex.org/W2983727866","https://openalex.org/W2986479369","https://openalex.org/W2989691494","https://openalex.org/W2997035654","https://openalex.org/W2998536339","https://openalex.org/W3003411605","https://openalex.org/W3006322515","https://openalex.org/W3034592098","https://openalex.org/W3091482797","https://openalex.org/W3105463831","https://openalex.org/W3115481010","https://openalex.org/W3174856432","https://openalex.org/W4230108479","https://openalex.org/W4230143017","https://openalex.org/W4231070535","https://openalex.org/W4235232193","https://openalex.org/W4239529062","https://openalex.org/W4245101509","https://openalex.org/W4289665794","https://openalex.org/W4293665662","https://openalex.org/W4299851312","https://openalex.org/W6631190155","https://openalex.org/W6637373629","https://openalex.org/W6680012447","https://openalex.org/W6729280921","https://openalex.org/W6729831399","https://openalex.org/W6740195615","https://openalex.org/W6760905588","https://openalex.org/W6764040762","https://openalex.org/W6767657221","https://openalex.org/W6767885514","https://openalex.org/W6786857951"],"related_works":["https://openalex.org/W2135359786","https://openalex.org/W2058170566","https://openalex.org/W2755342338","https://openalex.org/W2772917594","https://openalex.org/W2166024367","https://openalex.org/W3116076068","https://openalex.org/W2229312674","https://openalex.org/W2951359407","https://openalex.org/W2079911747","https://openalex.org/W2113831239"],"abstract_inverted_index":{"Reflective":[0],"and":[1,8,21,39,49,71,82,90,96,111,118,130,138,155],"textureless":[2],"surfaces":[3,113,137],"such":[4],"as":[5],"windows,":[6],"mirrors,":[7],"walls":[9],"can":[10],"be":[11],"a":[12],"challenge":[13],"for":[14,42,62,65,88,166],"scene":[15,44,67,106,164],"reconstruction,":[16],"due":[17],"to":[18,34,159],"depth":[19,37,94,115,153],"discontinuities":[20],"holes.":[22],"We":[23],"propose":[24],"an":[25],"audio-visual":[26,63,83],"method":[27],"that":[28],"uses":[29],"the":[30,74,125],"reflections":[31],"of":[32,120,151],"sound":[33,70,91,122],"aid":[35],"in":[36,46,124,162],"estimation":[38],"material":[40,97],"classification":[41,64,150],"3D":[43,66,105,163],"reconstruction":[45,165],"robot":[47,167],"navigation":[48],"AR/VR":[50],"applications.":[51],"The":[52,99],"mobile":[53],"phone":[54],"prototype":[55],"emits":[56],"pulsed":[57],"audio,":[58],"while":[59],"recording":[60],"video":[61,75],"reconstruction.":[68],"Reflected":[69],"images":[72],"from":[73,101,133],"are":[76],"input":[77],"into":[78],"our":[79],"audio":[80],"(EchoCNN-A)":[81],"(EchoCNN-AV)":[84],"convolutional":[85],"neural":[86],"networks":[87],"surface":[89],"source":[92],"detection,":[93],"estimation,":[95,154],"classification.":[98],"inferences":[100],"these":[102],"classifications":[103],"enhance":[104],"reconstructions":[107],"containing":[108],"open":[109],"spaces":[110],"reflective":[112],"by":[114],"filtering,":[116],"inpainting,":[117],"placement":[119],"unmixed":[121],"sources":[123],"scene.":[126],"Our":[127],"prototype,":[128],"demos,":[129],"experimental":[131],"results":[132],"real-world":[134],"with":[135,142],"challenging":[136],"sound,":[139],"also":[140],"validated":[141],"virtual":[143],"scenes,":[144],"indicate":[145],"high":[146],"success":[147],"rates":[148],"on":[149],"material,":[152],"closed/open":[156],"surfaces,":[157],"leading":[158],"considerable":[160],"improvement":[161],"navigation.":[168]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
