{"id":"https://openalex.org/W2952366764","doi":"https://doi.org/10.1109/icip.2018.8451134","title":"Inertia Sensor Aided Alignment for Burst Pipeline in Low Light Conditions","display_name":"Inertia Sensor Aided Alignment for Burst Pipeline in Low Light Conditions","publication_year":2018,"publication_date":"2018-09-07","ids":{"openalex":"https://openalex.org/W2952366764","doi":"https://doi.org/10.1109/icip.2018.8451134","mag":"2952366764"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2018.8451134","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2018.8451134","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 25th IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1811.02013","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100321549","display_name":"Shuang Zhang","orcid":"https://orcid.org/0000-0001-7471-6165"},"institutions":[{"id":"https://openalex.org/I107639228","display_name":"University of Notre Dame","ror":"https://ror.org/00mkhxb43","country_code":"US","type":"education","lineage":["https://openalex.org/I107639228"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Shuang Zhang","raw_affiliation_strings":["University of Notre Dame, Notre Dame, IN"],"affiliations":[{"raw_affiliation_string":"University of Notre Dame, Notre Dame, IN","institution_ids":["https://openalex.org/I107639228"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5088641046","display_name":"Robert Louis Stevenson","orcid":"https://orcid.org/0000-0002-2701-8249"},"institutions":[{"id":"https://openalex.org/I107639228","display_name":"University of Notre Dame","ror":"https://ror.org/00mkhxb43","country_code":"US","type":"education","lineage":["https://openalex.org/I107639228"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Robert L. Stevenson","raw_affiliation_strings":["University of Notre Dame, Notre Dame, IN"],"affiliations":[{"raw_affiliation_string":"University of Notre Dame, Notre Dame, IN","institution_ids":["https://openalex.org/I107639228"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5100321549"],"corresponding_institution_ids":["https://openalex.org/I107639228"],"apc_list":null,"apc_paid":null,"fwci":0.9212,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.76942532,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":"29","issue":null,"first_page":"3953","last_page":"3957"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11220","display_name":"Water Systems and Optimization","score":0.9918000102043152,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11220","display_name":"Water Systems and Optimization","score":0.9918000102043152,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural 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/T11019","display_name":"Image Enhancement Techniques","score":0.9897000193595886,"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9814000129699707,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/inertia","display_name":"Inertia","score":0.685853898525238},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.6401388645172119},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4973781406879425},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.32047003507614136},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.26451289653778076},{"id":"https://openalex.org/keywords/classical-mechanics","display_name":"Classical mechanics","score":0.09438565373420715}],"concepts":[{"id":"https://openalex.org/C110407247","wikidata":"https://www.wikidata.org/wiki/Q122508","display_name":"Inertia","level":2,"score":0.685853898525238},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.6401388645172119},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4973781406879425},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.32047003507614136},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.26451289653778076},{"id":"https://openalex.org/C74650414","wikidata":"https://www.wikidata.org/wiki/Q11397","display_name":"Classical mechanics","level":1,"score":0.09438565373420715},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icip.2018.8451134","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2018.8451134","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 25th IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1811.02013","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1811.02013","pdf_url":"https://arxiv.org/pdf/1811.02013","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1811.02013","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1811.02013","pdf_url":"https://arxiv.org/pdf/1811.02013","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1677409904","https://openalex.org/W1749494163","https://openalex.org/W1988446025","https://openalex.org/W1992989752","https://openalex.org/W1999046526","https://openalex.org/W2003007626","https://openalex.org/W2020491444","https://openalex.org/W2020934227","https://openalex.org/W2023005931","https://openalex.org/W2023585283","https://openalex.org/W2024763827","https://openalex.org/W2033819227","https://openalex.org/W2034251649","https://openalex.org/W2151103935","https://openalex.org/W2511026390","https://openalex.org/W2552290192","https://openalex.org/W2727642811","https://openalex.org/W2962767526","https://openalex.org/W4251178070","https://openalex.org/W6637400245","https://openalex.org/W6655473528"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W1979758163","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052","https://openalex.org/W4402327032"],"abstract_inverted_index":{"Merging":[0],"short-exposure":[1],"frames":[2],"can":[3],"provide":[4,108],"an":[5,23,34],"image":[6],"with":[7,125,142],"reduced":[8],"noise":[9],"in":[10],"low":[11],"light":[12],"conditions.":[13],"However,":[14],"how":[15],"best":[16],"to":[17,94,107,135],"align":[18],"images":[19],"before":[20],"merging":[21],"is":[22,62,105],"open":[24],"problem.":[25],"To":[26,51],"improve":[27],"the":[28,96,117,132],"performance":[29],"of":[30,99,122],"alignment,":[31],"we":[32],"propose":[33],"inertia-sensor":[35],"aided":[36],"algorithm":[37,118],"for":[38],"smartphone":[39,69],"burst":[40],"photography,":[41],"which":[42],"takes":[43],"rotation":[44,60,88],"and":[45,72,90,138],"out-plane":[46],"relative":[47,128],"movement":[48],"into":[49],"account.":[50],"calculate":[52],"homography":[53,112],"between":[54],"frames,":[55],"a":[56,109,120],"three":[57,59,73],"by":[58,68,79],"matrix":[61,89],"calculated":[63],"from":[64,84],"gyro":[65],"data":[66],"recorded":[67],"inertia":[70],"sensor":[71],"dimensional":[74],"translation":[75],"vector":[76],"are":[77,92],"estimated":[78],"matched":[80],"feature":[81],"points":[82],"detected":[83],"two":[85],"frames.":[86],"The":[87],"translations":[91],"combined":[93],"form":[95],"initial":[97],"guess":[98],"homography.":[100],"An":[101],"unscented":[102],"Kalman":[103],"filter":[104],"utilized":[106],"more":[110],"accurate":[111],"estimation.":[113],"We":[114,130],"have":[115],"tested":[116],"on":[119],"variety":[121],"different":[123,126],"scenes":[124],"camera":[127],"motions.":[129],"compare":[131],"proposed":[133],"method":[134],"benchmark":[136],"single-image":[137],"multi-image":[139],"denoising":[140],"methods":[141],"favourable":[143],"results.":[144]},"counts_by_year":[{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}