{"id":"https://openalex.org/W3000523248","doi":"https://doi.org/10.1109/lra.2020.2967307","title":"Towards Privacy-Preserving Ego-Motion Estimation Using an Extremely Low-Resolution Camera","display_name":"Towards Privacy-Preserving Ego-Motion Estimation Using an Extremely Low-Resolution Camera","publication_year":2020,"publication_date":"2020-01-17","ids":{"openalex":"https://openalex.org/W3000523248","doi":"https://doi.org/10.1109/lra.2020.2967307","mag":"3000523248"},"language":"en","primary_location":{"id":"doi:10.1109/lra.2020.2967307","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lra.2020.2967307","pdf_url":null,"source":{"id":"https://openalex.org/S4210169774","display_name":"IEEE Robotics and Automation Letters","issn_l":"2377-3766","issn":["2377-3766"],"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 Robotics and Automation 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/A5065505359","display_name":"Armon Shariati","orcid":"https://orcid.org/0000-0003-1812-6675"},"institutions":[{"id":"https://openalex.org/I79576946","display_name":"University of Pennsylvania","ror":"https://ror.org/00b30xv10","country_code":"US","type":"education","lineage":["https://openalex.org/I79576946"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Armon Shariati","raw_affiliation_strings":["GRASP Lab, School of Engineering and Applied Science, University of Pennsylvania, Edgewater, USA"],"raw_orcid":"https://orcid.org/0000-0003-1812-6675","affiliations":[{"raw_affiliation_string":"GRASP Lab, School of Engineering and Applied Science, University of Pennsylvania, Edgewater, USA","institution_ids":["https://openalex.org/I79576946"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046815740","display_name":"Christian Holz","orcid":"https://orcid.org/0000-0001-9655-9519"},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Christian Holz","raw_affiliation_strings":["Microsoft Research, Redmond, USA"],"raw_orcid":"https://orcid.org/0000-0001-9655-9519","affiliations":[{"raw_affiliation_string":"Microsoft Research, Redmond, USA","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5090341044","display_name":"Sudipta N. Sinha","orcid":"https://orcid.org/0000-0002-4186-3289"},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sudipta Sinha","raw_affiliation_strings":["Microsoft Research, Redmond, USA"],"raw_orcid":"https://orcid.org/0000-0002-4186-3289","affiliations":[{"raw_affiliation_string":"Microsoft Research, Redmond, USA","institution_ids":["https://openalex.org/I1290206253"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.3833,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.59230441,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"5","issue":"2","first_page":"1223","last_page":"1230"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":0.9998999834060669,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9998999834060669,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.9994000196456909,"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/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9962000250816345,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental 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":0.6761535406112671},{"id":"https://openalex.org/keywords/id-ego-and-super-ego","display_name":"Id, ego and super-ego","score":0.6045785546302795},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5965506434440613},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5390263199806213},{"id":"https://openalex.org/keywords/estimation","display_name":"Estimation","score":0.5045725107192993},{"id":"https://openalex.org/keywords/motion-estimation","display_name":"Motion estimation","score":0.44602739810943604},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.4387567639350891},{"id":"https://openalex.org/keywords/computer-graphics","display_name":"Computer graphics (images)","score":0.3645177483558655},{"id":"https://openalex.org/keywords/internet-privacy","display_name":"Internet privacy","score":0.3452689051628113},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.23412027955055237},{"id":"https://openalex.org/keywords/social-psychology","display_name":"Social psychology","score":0.12520331144332886},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.12115049362182617}],"concepts":[{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6761535406112671},{"id":"https://openalex.org/C9180747","wikidata":"https://www.wikidata.org/wiki/Q486893","display_name":"Id, ego and super-ego","level":2,"score":0.6045785546302795},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5965506434440613},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5390263199806213},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.5045725107192993},{"id":"https://openalex.org/C10161872","wikidata":"https://www.wikidata.org/wiki/Q557891","display_name":"Motion estimation","level":2,"score":0.44602739810943604},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.4387567639350891},{"id":"https://openalex.org/C121684516","wikidata":"https://www.wikidata.org/wiki/Q7600677","display_name":"Computer graphics (images)","level":1,"score":0.3645177483558655},{"id":"https://openalex.org/C108827166","wikidata":"https://www.wikidata.org/wiki/Q175975","display_name":"Internet privacy","level":1,"score":0.3452689051628113},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.23412027955055237},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.12520331144332886},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.12115049362182617},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lra.2020.2967307","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lra.2020.2967307","pdf_url":null,"source":{"id":"https://openalex.org/S4210169774","display_name":"IEEE Robotics and Automation Letters","issn_l":"2377-3766","issn":["2377-3766"],"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 Robotics and Automation Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":60,"referenced_works":["https://openalex.org/W612478963","https://openalex.org/W764651262","https://openalex.org/W1513100184","https://openalex.org/W1578285471","https://openalex.org/W1607376735","https://openalex.org/W1612997784","https://openalex.org/W1885185971","https://openalex.org/W1921093919","https://openalex.org/W1970504153","https://openalex.org/W1981990039","https://openalex.org/W1992989752","https://openalex.org/W2007963058","https://openalex.org/W2035379092","https://openalex.org/W2056358962","https://openalex.org/W2065336436","https://openalex.org/W2087380704","https://openalex.org/W2091790851","https://openalex.org/W2097074225","https://openalex.org/W2100315781","https://openalex.org/W2103031616","https://openalex.org/W2118223742","https://openalex.org/W2118877769","https://openalex.org/W2140599684","https://openalex.org/W2150066425","https://openalex.org/W2151290401","https://openalex.org/W2165939075","https://openalex.org/W2194775991","https://openalex.org/W2259424905","https://openalex.org/W2296147781","https://openalex.org/W2474281075","https://openalex.org/W2476548250","https://openalex.org/W2482726005","https://openalex.org/W2548527721","https://openalex.org/W2561074213","https://openalex.org/W2562066862","https://openalex.org/W2564632156","https://openalex.org/W2604246144","https://openalex.org/W2608018946","https://openalex.org/W2745859992","https://openalex.org/W2751023760","https://openalex.org/W2794966952","https://openalex.org/W2883702102","https://openalex.org/W2951881930","https://openalex.org/W2963243246","https://openalex.org/W2963372104","https://openalex.org/W2963470893","https://openalex.org/W2963782415","https://openalex.org/W2964123261","https://openalex.org/W2964140947","https://openalex.org/W2973990459","https://openalex.org/W3098068165","https://openalex.org/W3100388886","https://openalex.org/W3103648783","https://openalex.org/W3125449081","https://openalex.org/W4243425824","https://openalex.org/W6618872416","https://openalex.org/W6630726011","https://openalex.org/W6677548441","https://openalex.org/W6736260464","https://openalex.org/W6767470710"],"related_works":["https://openalex.org/W4317827682","https://openalex.org/W2384047230","https://openalex.org/W2349664984","https://openalex.org/W129516394","https://openalex.org/W3151918114","https://openalex.org/W2912578624","https://openalex.org/W2949426115","https://openalex.org/W2359694826","https://openalex.org/W2971369648","https://openalex.org/W2742105664"],"abstract_inverted_index":{"Ego-motion":[0],"estimation":[1],"is":[2,19,64,121,151,229],"a":[3,98,114,124,134,140],"core":[4],"task":[5],"in":[6,12,45,60,123],"robotic":[7],"systems":[8],"as":[9,11],"well":[10],"augmented":[13],"and":[14,36,48,191,199,226,234],"virtual":[15],"reality":[16],"applications.":[17],"It":[18],"often":[20],"solved":[21],"using":[22,27,127],"visual-inertial":[23],"odometry,":[24],"which":[25,50,176],"involves":[26],"one":[28],"or":[29],"more":[30],"always-on":[31],"cameras":[32],"on":[33,144,196],"mobile":[34],"robots":[35],"wearable":[37],"devices.":[38],"As":[39],"consumers":[40],"increasingly":[41],"use":[42,162],"such":[43,61],"devices":[44],"their":[46],"homes":[47],"workplaces,":[49],"are":[51],"filled":[52],"with":[53,156,236],"sensitive":[54],"details,":[55],"the":[56,74,166,180,197,237],"role":[57],"of":[58,65,142],"privacy":[59],"camera-based":[62],"approaches":[63],"ever":[66],"increasing":[67],"importance.":[68],"In":[69],"this":[70],"letter,":[71],"we":[72,161,177],"introduce":[73],"first":[75],"solution":[76],"to":[77,164],"perform":[78],"privacy-preserving":[79],"ego-motion":[80,214],"estimation.":[81],"We":[82,106,131,184],"recover":[83],"camera":[84,91,159,173,181,192,224],"egomotion":[85],"from":[86,171,175,216,231],"an":[87],"extremely":[88,217],"low-resolution":[89,218],"monocular":[90],"by":[92],"estimating":[93,111],"dense":[94],"optical":[95,129,188],"flow":[96,150,168,189],"at":[97],"higher":[99],"spatial":[100],"resolution":[101],"(i.e.,":[102],"4x":[103],"super":[104],"resolution).":[105],"propose":[107],"SRFNet":[108,143,163],"for":[109,138],"directly":[110],"Super-Resolved":[112],"Flow,":[113],"novel":[115],"convolutional":[116],"neural":[117],"network":[118],"model":[119],"that":[120,169,212],"trained":[122],"supervised":[125,136],"setting":[126],"ground-truth":[128],"flow.":[130],"also":[132],"present":[133],"weakly":[135],"approach":[137],"training":[139],"variant":[141],"real":[145],"videos":[146],"where":[147,203],"ground":[148],"truth":[149],"unavailable.":[152],"On":[153],"image":[154],"pairs":[155],"known":[157],"relative":[158],"orientations,":[160],"predict":[165],"auto-epipolar":[167],"arises":[170],"pure":[172],"translation,":[174],"robustly":[178],"estimate":[179],"translation":[182,193],"direction.":[183],"evaluate":[185],"our":[186,204],"super-resolved":[187],"estimates":[190,195],"direction":[194],"Sintel":[198],"KITTI":[200],"odometry":[201],"datasets,":[202],"methods":[205],"outperform":[206],"several":[207],"baselines.":[208],"Our":[209],"results":[210],"indicate":[211],"robust":[213],"recovery":[215],"images":[219],"can":[220],"be":[221],"viable":[222],"when":[223],"orientations":[225],"metric":[227],"scale":[228],"recovered":[230],"inertial":[232],"sensors":[233],"fused":[235],"estimated":[238],"translations.":[239]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}