{"id":"https://openalex.org/W4383754821","doi":"https://doi.org/10.1145/3570361.3592497","title":"QfaR: Location-Guided Scanning of Visual Codes from Long Distances","display_name":"QfaR: Location-Guided Scanning of Visual Codes from Long Distances","publication_year":2023,"publication_date":"2023-07-10","ids":{"openalex":"https://openalex.org/W4383754821","doi":"https://doi.org/10.1145/3570361.3592497"},"language":"en","primary_location":{"id":"doi:10.1145/3570361.3592497","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3570361.3592497","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 29th Annual International Conference on Mobile Computing and Networking","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/A5012439960","display_name":"Sizhuo Ma","orcid":"https://orcid.org/0000-0003-0092-9744"},"institutions":[{"id":"https://openalex.org/I4210142583","display_name":"Snap (United States)","ror":"https://ror.org/04dgkhg68","country_code":"US","type":"company","lineage":["https://openalex.org/I4210142583"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sizhuo Ma","raw_affiliation_strings":["Snap Inc., New York, New York, United States"],"raw_orcid":"https://orcid.org/0000-0003-0092-9744","affiliations":[{"raw_affiliation_string":"Snap Inc., New York, New York, United States","institution_ids":["https://openalex.org/I4210142583"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100370330","display_name":"Jian Wang","orcid":"https://orcid.org/0000-0001-5266-3808"},"institutions":[{"id":"https://openalex.org/I4210142583","display_name":"Snap (United States)","ror":"https://ror.org/04dgkhg68","country_code":"US","type":"company","lineage":["https://openalex.org/I4210142583"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jian Wang","raw_affiliation_strings":["Snap Inc., New York, New York, USA"],"raw_orcid":"https://orcid.org/0000-0001-5266-3808","affiliations":[{"raw_affiliation_string":"Snap Inc., New York, New York, USA","institution_ids":["https://openalex.org/I4210142583"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010254581","display_name":"Wenzheng Chen","orcid":"https://orcid.org/0009-0008-5623-1963"},"institutions":[{"id":"https://openalex.org/I185261750","display_name":"University of Toronto","ror":"https://ror.org/03dbr7087","country_code":"CA","type":"education","lineage":["https://openalex.org/I185261750"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Wenzheng Chen","raw_affiliation_strings":["University of Toronto, Toronto, Ontario, Canada"],"raw_orcid":"https://orcid.org/0009-0008-5623-1963","affiliations":[{"raw_affiliation_string":"University of Toronto, Toronto, Ontario, Canada","institution_ids":["https://openalex.org/I185261750"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018612025","display_name":"Suman Banerjee","orcid":"https://orcid.org/0000-0002-5548-8862"},"institutions":[{"id":"https://openalex.org/I135310074","display_name":"University of Wisconsin\u2013Madison","ror":"https://ror.org/01y2jtd41","country_code":"US","type":"education","lineage":["https://openalex.org/I135310074"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Suman Banerjee","raw_affiliation_strings":["University of Wisconsin-Madison, Madison, Wisconsin, United States"],"raw_orcid":"https://orcid.org/0000-0002-5548-8862","affiliations":[{"raw_affiliation_string":"University of Wisconsin-Madison, Madison, Wisconsin, United States","institution_ids":["https://openalex.org/I135310074"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074353153","display_name":"Mohit Gupta","orcid":"https://orcid.org/0000-0002-2323-7700"},"institutions":[{"id":"https://openalex.org/I135310074","display_name":"University of Wisconsin\u2013Madison","ror":"https://ror.org/01y2jtd41","country_code":"US","type":"education","lineage":["https://openalex.org/I135310074"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mohit Gupta","raw_affiliation_strings":["University of Wisconsin-Madison, Madison, Wisconsin, USA"],"raw_orcid":"https://orcid.org/0000-0002-2323-7700","affiliations":[{"raw_affiliation_string":"University of Wisconsin-Madison, Madison, Wisconsin, USA","institution_ids":["https://openalex.org/I135310074"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5051975921","display_name":"Shree K. Nayar","orcid":"https://orcid.org/0000-0002-6452-6998"},"institutions":[{"id":"https://openalex.org/I4210142583","display_name":"Snap (United States)","ror":"https://ror.org/04dgkhg68","country_code":"US","type":"company","lineage":["https://openalex.org/I4210142583"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shree Nayar","raw_affiliation_strings":["Snap Inc., New York, New York, USA"],"raw_orcid":"https://orcid.org/0000-0002-6452-6998","affiliations":[{"raw_affiliation_string":"Snap Inc., New York, New York, USA","institution_ids":["https://openalex.org/I4210142583"]}]}],"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":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"14"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11598","display_name":"Internet Traffic Analysis and Secure E-voting","score":0.9975000023841858,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11598","display_name":"Internet Traffic Analysis and Secure E-voting","score":0.9975000023841858,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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":0.9957000017166138,"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/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.9944999814033508,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8090549111366272},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.5889200568199158},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.502678394317627},{"id":"https://openalex.org/keywords/mobile-device","display_name":"Mobile device","score":0.4922882616519928},{"id":"https://openalex.org/keywords/android","display_name":"Android (operating system)","score":0.458261102437973},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4155004620552063}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8090549111366272},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.5889200568199158},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.502678394317627},{"id":"https://openalex.org/C186967261","wikidata":"https://www.wikidata.org/wiki/Q5082128","display_name":"Mobile device","level":2,"score":0.4922882616519928},{"id":"https://openalex.org/C557433098","wikidata":"https://www.wikidata.org/wiki/Q94","display_name":"Android (operating system)","level":2,"score":0.458261102437973},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4155004620552063},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3570361.3592497","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3570361.3592497","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 29th Annual International Conference on Mobile Computing and Networking","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1685258356","display_name":null,"funder_award_id":"70NANB21H043","funder_id":"https://openalex.org/F4320306111","funder_display_name":"U.S. Department of Commerce"},{"id":"https://openalex.org/G2534301439","display_name":null,"funder_award_id":"CNS-2107060","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G3757886611","display_name":"CNS Core: Medium: Characterization, Mitigation, and Management of Active 3D Camera Interference","funder_award_id":"2107060","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G4649966841","display_name":"MLWiNS: Distributed Learning for the Nomadic Edge","funder_award_id":"2003129","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G5246444745","display_name":"ECDI: Computation, Communication, and Storage Infrastructure For The Roaming Edge","funder_award_id":"1838733","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G6250460064","display_name":null,"funder_award_id":"CNS-1647152","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G7332606278","display_name":null,"funder_award_id":"CNS-1838733","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G7709164144","display_name":null,"funder_award_id":"CNS-2112562","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G7872055366","display_name":null,"funder_award_id":"CNS-2003129","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G7917285098","display_name":"US Ignite: Focus Area 2: An Infrastructure to support Edge Computing in the Extreme","funder_award_id":"1647152","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G8377316191","display_name":"AI Institute for Edge Computing Leveraging Next Generation Networks (Athena)","funder_award_id":"2112562","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320306111","display_name":"U.S. Department of Commerce","ror":"https://ror.org/04chq2495"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W154669480","https://openalex.org/W2100852839","https://openalex.org/W2104745266","https://openalex.org/W2148575324","https://openalex.org/W2162442687","https://openalex.org/W2165783425","https://openalex.org/W2412148585","https://openalex.org/W2963423786","https://openalex.org/W3018105153"],"related_works":["https://openalex.org/W2058170566","https://openalex.org/W2772917594","https://openalex.org/W2755342338","https://openalex.org/W2166024367","https://openalex.org/W3116076068","https://openalex.org/W2229312674","https://openalex.org/W2951359407","https://openalex.org/W2079911747","https://openalex.org/W1969923398","https://openalex.org/W2775347418"],"abstract_inverted_index":{"Visual":[0],"codes":[1,5,46,58,91,101,170,176,188],"such":[2,147],"as":[3,148],"QR":[4,216],"provide":[6],"a":[7,35,72,181,206],"low-cost":[8],"and":[9,16,25,92,158,186,198],"convenient":[10],"communication":[11],"channel":[12],"between":[13],"physical":[14,31,76],"objects":[15],"mobile":[17,41],"devices,":[18],"but":[19],"typically":[20],"operate":[21],"when":[22],"the":[23,26,52,56,86,90,93,97,114,124,128],"code":[24,67,116,126],"device":[27],"are":[28],"in":[29],"close":[30],"proximity.":[32],"We":[33],"propose":[34],"system,":[36],"called":[37],"QfaR,":[38],"which":[39,169],"enables":[40],"devices":[42,160],"to":[43,219],"scan":[44],"visual":[45,57,125],"across":[47],"long":[48],"distances":[49,167],"even":[50,108],"where":[51,69],"image":[53],"resolution":[54],"of":[55,75,78,89,99,183],"is":[59,63,83,95,140],"extremely":[60],"low.":[61],"QfaR":[62,120,139,163,193],"based":[64],"on":[65,210],"location-guided":[66],"scanning,":[68],"we":[70,203],"utilize":[71],"crowd-sourced":[73],"database":[74],"locations":[77],"codes.":[79],"Our":[80],"key":[81],"observation":[82],"that":[84,162],"if":[85,109],"approximate":[87],"location":[88],"user":[94],"known,":[96],"space":[98],"possible":[100],"can":[102,121,164,171,177],"be":[103,118,172,178],"dramatically":[104],"pruned":[105,129],"down.":[106],"Then,":[107],"every":[110],"\"single":[111],"bit\"":[112],"from":[113,127],"low-resolution":[115],"cannot":[117],"recovered,":[119],"still":[122],"identify":[123],"list":[130],"with":[131,155],"high":[132],"probability.":[133],"By":[134],"applying":[135],"computer":[136],"vision":[137],"techniques,":[138],"also":[141,204],"robust":[142],"against":[143],"challenging":[144],"imaging":[145],"conditions,":[146],"tilt,":[149],"motion":[150],"blur,":[151],"etc.":[152],"Experimental":[153],"results":[154],"common":[156],"iOS":[157],"Android":[159],"show":[161],"significantly":[165],"enhance":[166],"at":[168,180,189],"scanned,":[173],"e.g.,":[174],"3.6cm-sized":[175],"scanned":[179],"distance":[182],"7.5":[184],"meters,":[185],"0.5m-sized":[187],"about":[190],"100":[191],"meters.":[192],"has":[194],"many":[195],"potential":[196],"applications,":[197],"beyond":[199],"our":[200],"diverse":[201],"experiments,":[202],"conduct":[205],"simple":[207],"case":[208],"study":[209],"its":[211],"use":[212],"for":[213],"efficiently":[214],"scanning":[215],"code-based":[217],"badges":[218],"estimate":[220],"event":[221],"attendance.":[222]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
