{"id":"https://openalex.org/W4389665603","doi":"https://doi.org/10.1109/iros55552.2023.10341758","title":"Converting Depth Images and Point Clouds for Feature-Based Pose Estimation","display_name":"Converting Depth Images and Point Clouds for Feature-Based Pose Estimation","publication_year":2023,"publication_date":"2023-10-01","ids":{"openalex":"https://openalex.org/W4389665603","doi":"https://doi.org/10.1109/iros55552.2023.10341758"},"language":"en","primary_location":{"id":"doi:10.1109/iros55552.2023.10341758","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros55552.2023.10341758","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","raw_type":"proceedings-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/A5071289351","display_name":"R. L\u00f6sch","orcid":"https://orcid.org/0009-0000-8627-3955"},"institutions":[{"id":"https://openalex.org/I61893789","display_name":"TU Bergakademie Freiberg","ror":"https://ror.org/031vc2293","country_code":"DE","type":"education","lineage":["https://openalex.org/I61893789"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Robert L\u00f6sch","raw_affiliation_strings":["Institute of Computer Science, Technical University Bergakademie,Freiberg,Germany","Institute of Computer Science, Technical University Bergakademie, Freiberg, Germany"],"affiliations":[{"raw_affiliation_string":"Institute of Computer Science, Technical University Bergakademie,Freiberg,Germany","institution_ids":["https://openalex.org/I61893789"]},{"raw_affiliation_string":"Institute of Computer Science, Technical University Bergakademie, Freiberg, Germany","institution_ids":["https://openalex.org/I61893789"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052424761","display_name":"Mark Sastuba","orcid":"https://orcid.org/0000-0002-6232-9536"},"institutions":[{"id":"https://openalex.org/I2800871051","display_name":"Federal Railway Authority","ror":"https://ror.org/0392kk689","country_code":"DE","type":"government","lineage":["https://openalex.org/I2800871051","https://openalex.org/I2800888199"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Mark Sastuba","raw_affiliation_strings":["German Centre for Rail Traffic Research at the Federal Railway Authority,Germany","German Centre for Rail Traffic Research at the Federal Railway Authority, Germany"],"affiliations":[{"raw_affiliation_string":"German Centre for Rail Traffic Research at the Federal Railway Authority,Germany","institution_ids":["https://openalex.org/I2800871051"]},{"raw_affiliation_string":"German Centre for Rail Traffic Research at the Federal Railway Authority, Germany","institution_ids":["https://openalex.org/I2800871051"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111062508","display_name":"Jonas Toth","orcid":null},"institutions":[{"id":"https://openalex.org/I61893789","display_name":"TU Bergakademie Freiberg","ror":"https://ror.org/031vc2293","country_code":"DE","type":"education","lineage":["https://openalex.org/I61893789"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Jonas Toth","raw_affiliation_strings":["Institute of Computer Science, Technical University Bergakademie,Freiberg,Germany","Institute of Computer Science, Technical University Bergakademie, Freiberg, Germany"],"affiliations":[{"raw_affiliation_string":"Institute of Computer Science, Technical University Bergakademie,Freiberg,Germany","institution_ids":["https://openalex.org/I61893789"]},{"raw_affiliation_string":"Institute of Computer Science, Technical University Bergakademie, Freiberg, Germany","institution_ids":["https://openalex.org/I61893789"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103960410","display_name":"Bernhard Jung","orcid":null},"institutions":[{"id":"https://openalex.org/I61893789","display_name":"TU Bergakademie Freiberg","ror":"https://ror.org/031vc2293","country_code":"DE","type":"education","lineage":["https://openalex.org/I61893789"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Bernhard Jung","raw_affiliation_strings":["Institute of Computer Science, Technical University Bergakademie,Freiberg,Germany","Institute of Computer Science, Technical University Bergakademie, Freiberg, Germany"],"affiliations":[{"raw_affiliation_string":"Institute of Computer Science, Technical University Bergakademie,Freiberg,Germany","institution_ids":["https://openalex.org/I61893789"]},{"raw_affiliation_string":"Institute of Computer Science, Technical University Bergakademie, Freiberg, Germany","institution_ids":["https://openalex.org/I61893789"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5071289351"],"corresponding_institution_ids":["https://openalex.org/I61893789"],"apc_list":null,"apc_paid":null,"fwci":1.7628,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.87279834,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"3422","last_page":"3428"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":1.0,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9987000226974487,"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/T11211","display_name":"3D Surveying and Cultural Heritage","score":0.9969000220298767,"subfield":{"id":"https://openalex.org/subfields/1907","display_name":"Geology"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.8374218940734863},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.7861950993537903},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7369741201400757},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.6234428882598877},{"id":"https://openalex.org/keywords/scale-invariant-feature-transform","display_name":"Scale-invariant feature transform","score":0.5876364707946777},{"id":"https://openalex.org/keywords/pose","display_name":"Pose","score":0.5653073787689209},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5459704399108887},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.5385452508926392},{"id":"https://openalex.org/keywords/visual-odometry","display_name":"Visual odometry","score":0.41954392194747925},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.3584129214286804},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.1665509045124054}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8374218940734863},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7861950993537903},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7369741201400757},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.6234428882598877},{"id":"https://openalex.org/C61265191","wikidata":"https://www.wikidata.org/wiki/Q767770","display_name":"Scale-invariant feature transform","level":3,"score":0.5876364707946777},{"id":"https://openalex.org/C52102323","wikidata":"https://www.wikidata.org/wiki/Q1671968","display_name":"Pose","level":2,"score":0.5653073787689209},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5459704399108887},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.5385452508926392},{"id":"https://openalex.org/C5799516","wikidata":"https://www.wikidata.org/wiki/Q4110915","display_name":"Visual odometry","level":3,"score":0.41954392194747925},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3584129214286804},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.1665509045124054},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iros55552.2023.10341758","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros55552.2023.10341758","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6499999761581421,"id":"https://metadata.un.org/sdg/13","display_name":"Climate action"}],"awards":[{"id":"https://openalex.org/G795986292","display_name":null,"funder_award_id":"17019","funder_id":"https://openalex.org/F4320332999","funder_display_name":"Horizon 2020 Framework Programme"}],"funders":[{"id":"https://openalex.org/F4320332999","display_name":"Horizon 2020 Framework Programme","ror":"https://ror.org/00k4n6c32"},{"id":"https://openalex.org/F4320337669","display_name":"H2020 European Institute of Innovation and Technology","ror":"https://ror.org/036dxts37"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1560733430","https://openalex.org/W2021851106","https://openalex.org/W2048710758","https://openalex.org/W2049981393","https://openalex.org/W2067681708","https://openalex.org/W2085261163","https://openalex.org/W2117228865","https://openalex.org/W2119605622","https://openalex.org/W2135797233","https://openalex.org/W2144092759","https://openalex.org/W2144367064","https://openalex.org/W2151103935","https://openalex.org/W2411681238","https://openalex.org/W2527172881","https://openalex.org/W2571024635","https://openalex.org/W2876324142","https://openalex.org/W3015235064","https://openalex.org/W3043971245","https://openalex.org/W3090923812","https://openalex.org/W3099455272","https://openalex.org/W3135301258","https://openalex.org/W3143504974","https://openalex.org/W4249866455","https://openalex.org/W6803376173"],"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/W2020188645","https://openalex.org/W2739923608","https://openalex.org/W4320086129","https://openalex.org/W2558322195"],"abstract_inverted_index":{"In":[0],"recent":[1],"years,":[2],"depth":[3,41,53,68,152],"sensors":[4],"have":[5,12],"become":[6],"more":[7,9,101,105],"and":[8,11,104,120,130,143,154],"affordable":[10],"found":[13],"their":[14],"way":[15],"into":[16,55,85],"a":[17,30,49,73,116],"growing":[18],"amount":[19],"of":[20,51,58,75,112],"robotic":[21],"systems.":[22],"However,":[23],"mono-":[24],"or":[25,43],"multi-modal":[26],"sensor":[27],"registration,":[28],"often":[29],"necessary":[31],"step":[32],"for":[33],"further":[34],"pro-cessing,":[35],"faces":[36],"many":[37],"challenges":[38],"on":[39],"raw":[40],"images":[42,56,99,135,142],"point":[44],"clouds.":[45],"This":[46],"paper":[47],"presents":[48],"method":[50,95],"converting":[52],"data":[54,153],"capable":[57],"visualizing":[59],"spatial":[60],"details":[61],"that":[62],"are":[63],"basically":[64],"hidden":[65],"in":[66,115],"traditional":[67],"images.":[69],"After":[70],"noise":[71],"removal,":[72],"neighborhood":[74],"points":[76],"forms":[77],"two":[78],"normal":[79],"vectors":[80],"whose":[81],"difference":[82],"is":[83,160],"encoded":[84],"this":[86],"new":[87,133],"conversion.":[88],"Compared":[89],"to":[90,147],"Bearing":[91,140],"Angle":[92,141],"images,":[93],"our":[94,132],"yields":[96],"brighter,":[97],"higher-contrast":[98],"with":[100],"visible":[102],"contours":[103],"details.":[106],"We":[107],"tested":[108,125],"feature-based":[109],"pose":[110],"estimation":[111],"both":[113],"conversions":[114],"visual":[117],"odometry":[118],"task":[119],"RGB-D":[121],"SLAM.":[122],"For":[123],"all":[124],"features,":[126],"AKAZE,":[127],"ORB,":[128],"SIFT,":[129],"SURF,":[131],"Flexion":[134],"yield":[136],"better":[137],"results":[138],"than":[139],"show":[144],"great":[145],"potential":[146],"bridge":[148],"the":[149],"gap":[150],"between":[151],"classical":[155],"computer":[156],"vision.":[157],"Source":[158],"code":[159],"available":[161],"here:":[162],"https://rlsch.github.io/depth-flexion-conversion.":[163]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2023-12-14T00:00:00"}