{"id":"https://openalex.org/W2534894314","doi":"https://doi.org/10.1109/globalsip.2013.6737002","title":"Workload analysis and efficient OpenCL-based implementation of SIFT algorithm on a smartphone","display_name":"Workload analysis and efficient OpenCL-based implementation of SIFT algorithm on a smartphone","publication_year":2013,"publication_date":"2013-12-01","ids":{"openalex":"https://openalex.org/W2534894314","doi":"https://doi.org/10.1109/globalsip.2013.6737002","mag":"2534894314"},"language":"en","primary_location":{"id":"doi:10.1109/globalsip.2013.6737002","is_oa":false,"landing_page_url":"https://doi.org/10.1109/globalsip.2013.6737002","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE Global Conference on Signal and Information Processing","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/A5100642258","display_name":"Guohui Wang","orcid":"https://orcid.org/0000-0002-3176-317X"},"institutions":[{"id":"https://openalex.org/I74775410","display_name":"Rice University","ror":"https://ror.org/008zs3103","country_code":"US","type":"education","lineage":["https://openalex.org/I74775410"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Guohui Wang","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Rice University, Houston, Texas"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Rice University, Houston, Texas","institution_ids":["https://openalex.org/I74775410"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056042800","display_name":"Blaine Rister","orcid":"https://orcid.org/0000-0002-4490-0444"},"institutions":[{"id":"https://openalex.org/I74775410","display_name":"Rice University","ror":"https://ror.org/008zs3103","country_code":"US","type":"education","lineage":["https://openalex.org/I74775410"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Blaine Rister","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Rice University, Houston, Texas"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Rice University, Houston, Texas","institution_ids":["https://openalex.org/I74775410"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5085983829","display_name":"Joseph R. Cavallaro","orcid":"https://orcid.org/0000-0002-9841-1806"},"institutions":[{"id":"https://openalex.org/I74775410","display_name":"Rice University","ror":"https://ror.org/008zs3103","country_code":"US","type":"education","lineage":["https://openalex.org/I74775410"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Joseph R. Cavallaro","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Rice University, Houston, Texas"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Rice University, Houston, Texas","institution_ids":["https://openalex.org/I74775410"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I74775410"],"apc_list":null,"apc_paid":null,"fwci":4.3653,"has_fulltext":false,"cited_by_count":40,"citation_normalized_percentile":{"value":0.9614334,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"759","last_page":"762"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":1.0,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":1.0,"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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9976000189781189,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9958999752998352,"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/scale-invariant-feature-transform","display_name":"Scale-invariant feature transform","score":0.8947270512580872},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.892243504524231},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4903590679168701},{"id":"https://openalex.org/keywords/mobile-device","display_name":"Mobile device","score":0.42248255014419556},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4166163206100464},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.3716725707054138},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3198651373386383}],"concepts":[{"id":"https://openalex.org/C61265191","wikidata":"https://www.wikidata.org/wiki/Q767770","display_name":"Scale-invariant feature transform","level":3,"score":0.8947270512580872},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.892243504524231},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4903590679168701},{"id":"https://openalex.org/C186967261","wikidata":"https://www.wikidata.org/wiki/Q5082128","display_name":"Mobile device","level":2,"score":0.42248255014419556},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4166163206100464},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.3716725707054138},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3198651373386383},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/globalsip.2013.6737002","is_oa":false,"landing_page_url":"https://doi.org/10.1109/globalsip.2013.6737002","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE Global Conference on Signal and Information Processing","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.384.8178","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.384.8178","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.ece.rice.edu/~gw2/pdf/globalsip2013_sift_mobile_gpu.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7","score":0.9100000262260437}],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320332195","display_name":"Samsung","ror":"https://ror.org/04w3jy968"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W1972807703","https://openalex.org/W2040219967","https://openalex.org/W2066941820","https://openalex.org/W2083822463","https://openalex.org/W2119605622","https://openalex.org/W2132079375","https://openalex.org/W2151103935","https://openalex.org/W2152724437","https://openalex.org/W2177274842","https://openalex.org/W2407803746","https://openalex.org/W6713734010"],"related_works":["https://openalex.org/W3034955165","https://openalex.org/W2094920358","https://openalex.org/W2041448692","https://openalex.org/W2247121321","https://openalex.org/W2391926582","https://openalex.org/W1966831329","https://openalex.org/W1995688991","https://openalex.org/W2020188645","https://openalex.org/W2739923608","https://openalex.org/W2049930962"],"abstract_inverted_index":{"Feature":[0,19],"detection":[1,175],"and":[2,14,32,69,98,115,141,151,176,186],"extraction":[3],"are":[4,167],"essential":[5],"in":[6,56,143],"computer":[7],"vision":[8],"applications":[9],"such":[10,66],"as":[11,67],"image":[12],"matching":[13],"object":[15],"recognition.":[16],"The":[17,161],"Scale-Invariant":[18],"Transform":[20],"(SIFT)":[21],"algorithm":[22,50,82,109,137],"is":[23],"one":[24],"of":[25,79,88,106,125,189],"the":[26,48,80,89,95,100,107,123,130,135,139,149,153,184,187,190,193],"most":[27],"robust":[28],"approaches":[29],"to":[30,46,51,121,157,169,203],"detect":[31],"extract":[33],"distinctive":[34],"invariant":[35],"features":[36],"from":[37],"images.":[38],"However,":[39],"high":[40],"computational":[41],"complexity":[42],"makes":[43],"it":[44],"difficult":[45],"apply":[47],"SIFT":[49,81,96,108,136],"mobile":[52,57,64,90,119],"applications.":[53],"Recent":[54],"developments":[55],"processors":[58],"have":[59],"enabled":[60],"heterogeneous":[61,194],"computing":[62],"on":[63,83,129],"devices,":[65],"smartphones":[68],"tablets.":[70],"In":[71],"this":[72],"paper,":[73],"we":[74,133,166],"present":[75],"an":[76,204],"OpenCL-based":[77],"implementation":[78,195],"a":[84,144],"smartphone,":[85],"taking":[86],"advantage":[87],"GPU.":[91],"We":[92,102],"carefully":[93],"analyze":[94],"workloads":[97],"identify":[99],"parallelism.":[101],"implemented":[103],"major":[104],"steps":[105],"using":[110],"both":[111],"serial":[112],"C++":[113],"code":[114],"OpenCL":[116],"kernels":[117],"targeting":[118],"processors,":[120],"compare":[122],"performance":[124],"different":[126],"workflows.":[127],"Based":[128],"profiling":[131],"results,":[132],"partition":[134],"between":[138],"CPU":[140],"GPU":[142],"way":[145],"that":[146,165],"best":[147],"exploits":[148],"parallelism":[150],"minimizes":[152],"buffer":[154],"transferring":[155],"time":[156],"achieve":[158,170],"better":[159],"performance.":[160],"experimental":[162],"results":[163],"show":[164],"able":[168],"8.5":[171],"FPS":[172,178],"for":[173,179],"keypoints":[174],"19":[177],"descriptor":[180],"generation":[181],"without":[182],"reducing":[183],"number":[185],"quality":[188],"keypoints.":[191],"Moreover,":[192],"can":[196],"reduce":[197],"energy":[198],"consumption":[199],"by":[200],"41%":[201],"compared":[202],"optimized":[205],"CPU-only":[206],"implementation.":[207]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":5},{"year":2017,"cited_by_count":6},{"year":2016,"cited_by_count":6},{"year":2015,"cited_by_count":7},{"year":2014,"cited_by_count":8}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}