{"id":"https://openalex.org/W2980680947","doi":"https://doi.org/10.1109/ispa.2019.8868792","title":"On the Comparison of Classic and Deep Keypoint Detector and Descriptor Methods","display_name":"On the Comparison of Classic and Deep Keypoint Detector and Descriptor Methods","publication_year":2019,"publication_date":"2019-09-01","ids":{"openalex":"https://openalex.org/W2980680947","doi":"https://doi.org/10.1109/ispa.2019.8868792","mag":"2980680947"},"language":"en","primary_location":{"id":"doi:10.1109/ispa.2019.8868792","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ispa.2019.8868792","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 11th International Symposium on Image and Signal Processing and Analysis (ISPA)","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2007.10000","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"David Bojanic","orcid":null},"institutions":[{"id":"https://openalex.org/I181343428","display_name":"University of Zagreb","ror":"https://ror.org/00mv6sv71","country_code":"HR","type":"education","lineage":["https://openalex.org/I181343428"]}],"countries":["HR"],"is_corresponding":true,"raw_author_name":"David Bojanic","raw_affiliation_strings":["Faculty of Electrical Engineering and Computing, University of Zagreb, Zagreb, Croatia, EU"],"affiliations":[{"raw_affiliation_string":"Faculty of Electrical Engineering and Computing, University of Zagreb, Zagreb, Croatia, EU","institution_ids":["https://openalex.org/I181343428"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Kristijan Bartol","orcid":null},"institutions":[{"id":"https://openalex.org/I181343428","display_name":"University of Zagreb","ror":"https://ror.org/00mv6sv71","country_code":"HR","type":"education","lineage":["https://openalex.org/I181343428"]}],"countries":["HR"],"is_corresponding":false,"raw_author_name":"Kristijan Bartol","raw_affiliation_strings":["Faculty of Electrical Engineering and Computing, University of Zagreb, Zagreb, Croatia, EU"],"affiliations":[{"raw_affiliation_string":"Faculty of Electrical Engineering and Computing, University of Zagreb, Zagreb, Croatia, EU","institution_ids":["https://openalex.org/I181343428"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Tomislav Pribanic","orcid":null},"institutions":[{"id":"https://openalex.org/I181343428","display_name":"University of Zagreb","ror":"https://ror.org/00mv6sv71","country_code":"HR","type":"education","lineage":["https://openalex.org/I181343428"]}],"countries":["HR"],"is_corresponding":false,"raw_author_name":"Tomislav Pribanic","raw_affiliation_strings":["Faculty of Electrical Engineering and Computing, University of Zagreb, Zagreb, Croatia, EU"],"affiliations":[{"raw_affiliation_string":"Faculty of Electrical Engineering and Computing, University of Zagreb, Zagreb, Croatia, EU","institution_ids":["https://openalex.org/I181343428"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Tomislav Petkovic","orcid":null},"institutions":[{"id":"https://openalex.org/I181343428","display_name":"University of Zagreb","ror":"https://ror.org/00mv6sv71","country_code":"HR","type":"education","lineage":["https://openalex.org/I181343428"]}],"countries":["HR"],"is_corresponding":false,"raw_author_name":"Tomislav Petkovic","raw_affiliation_strings":["Faculty of Electrical Engineering and Computing, University of Zagreb, Zagreb, Croatia, EU"],"affiliations":[{"raw_affiliation_string":"Faculty of Electrical Engineering and Computing, University of Zagreb, Zagreb, Croatia, EU","institution_ids":["https://openalex.org/I181343428"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Yago Diez Donoso","orcid":null},"institutions":[{"id":"https://openalex.org/I112524849","display_name":"Yamagata University","ror":"https://ror.org/00xy44n04","country_code":"JP","type":"education","lineage":["https://openalex.org/I112524849"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yago Diez Donoso","raw_affiliation_strings":["Faculty of Science, Yamagata University, Yamagata, Japan"],"affiliations":[{"raw_affiliation_string":"Faculty of Science, Yamagata University, Yamagata, Japan","institution_ids":["https://openalex.org/I112524849"]}]},{"author_position":"last","author":{"id":null,"display_name":"Joaquim Salvi Mas","orcid":null},"institutions":[{"id":"https://openalex.org/I251424209","display_name":"University of Girona","ror":"https://ror.org/01xdxns91","country_code":"ES","type":"education","lineage":["https://openalex.org/I251424209"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Joaquim Salvi Mas","raw_affiliation_strings":["Department of Computer Architecture and Technology, University of Girona, Girona, Spain, EU"],"affiliations":[{"raw_affiliation_string":"Department of Computer Architecture and Technology, University of Girona, Girona, Spain, EU","institution_ids":["https://openalex.org/I251424209"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I181343428"],"apc_list":null,"apc_paid":null,"fwci":0.8175,"has_fulltext":false,"cited_by_count":32,"citation_normalized_percentile":{"value":0.77756347,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"64","last_page":"69"},"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":0.9998000264167786,"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":0.9998000264167786,"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/T12389","display_name":"Infrared Target Detection Methodologies","score":0.9968000054359436,"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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.991599977016449,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/perspective","display_name":"Perspective (graphical)","score":0.6004999876022339},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5866000056266785},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.5656999945640564},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.5450000166893005},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4984000027179718},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4650999903678894}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7915999889373779},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6067000031471252},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.6004999876022339},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5866000056266785},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.5656999945640564},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5540000200271606},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.5450000166893005},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4984000027179718},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4650999903678894},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4059999883174896},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.36559998989105225},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.32109999656677246},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.29589998722076416},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.2583000063896179},{"id":"https://openalex.org/C2986492983","wikidata":"https://www.wikidata.org/wiki/Q861092","display_name":"Image matching","level":3,"score":0.25450000166893005},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.25110000371932983}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/ispa.2019.8868792","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ispa.2019.8868792","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 11th International Symposium on Image and Signal Processing and Analysis (ISPA)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2007.10000","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2007.10000","pdf_url":"https://arxiv.org/pdf/2007.10000","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:2007.10000","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2007.10000","pdf_url":"https://arxiv.org/pdf/2007.10000","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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W1532362218","https://openalex.org/W1596812151","https://openalex.org/W1849277567","https://openalex.org/W1979931042","https://openalex.org/W1980911747","https://openalex.org/W1995266040","https://openalex.org/W2028394888","https://openalex.org/W2048710758","https://openalex.org/W2111308925","https://openalex.org/W2117228865","https://openalex.org/W2124404372","https://openalex.org/W2141584146","https://openalex.org/W2151103935","https://openalex.org/W2177274842","https://openalex.org/W2294208686","https://openalex.org/W2802865601","https://openalex.org/W2963748588","https://openalex.org/W6629564929","https://openalex.org/W6637400245","https://openalex.org/W6679388247","https://openalex.org/W6685266013","https://openalex.org/W6747043499","https://openalex.org/W6752208963","https://openalex.org/W6753563816","https://openalex.org/W6759057345","https://openalex.org/W6803376173"],"related_works":[],"abstract_inverted_index":{"The":[0,106],"purpose":[1],"of":[2,48,61,129,133],"this":[3],"study":[4],"is":[5,51,138],"to":[6],"give":[7],"a":[8,46],"performance":[9,60,94],"comparison":[10],"between":[11],"several":[12],"classic":[13,111,120],"hand-crafted":[14],"and":[15,19,43,64,70,82,88,103,112],"deep":[16,66,113,125],"key-point":[17],"detector":[18],"descriptor":[20],"methods.":[21],"In":[22,127],"particular,":[23],"we":[24,57],"consider":[25],"the":[26,59,76,93,130,139],"following":[27],"classical":[28],"algorithms:":[29],"SIFT,":[30],"SURF,":[31],"ORB,":[32],"FAST,":[33],"BRISK,":[34],"MSER,":[35],"HARRIS,":[36],"KAZE,":[37],"AKAZE,":[38],"AGAST,":[39],"GFTT,":[40],"FREAK,":[41],"BRIEF":[42],"RootSIFT,":[44],"where":[45],"subset":[47],"all":[49],"combinations":[50,122],"paired":[52],"into":[53],"detector-descriptor":[54,67,121],"pipelines.":[55],"Additionally,":[56],"analyze":[58,92],"two":[62],"recent":[63],"perspective":[65],"models,":[68],"LF-Net":[69],"SuperPoint.":[71],"Our":[72],"benchmark":[73],"relies":[74],"on":[75,95],"HPSequences":[77],"dataset":[78],"that":[79,109],"provides":[80],"real":[81],"diverse":[83],"images":[84],"under":[85],"various":[86],"geometric":[87],"illumination":[89],"changes.":[90],"We":[91],"three":[96],"evaluation":[97],"tasks:":[98],"keypoint":[99,104],"verification,":[100],"image":[101],"matching":[102],"retrieval.":[105],"results":[107],"show":[108],"certain":[110],"approaches":[114],"are":[115],"still":[116],"comparable,":[117],"with":[118],"some":[119],"overperforming":[123],"pretrained":[124],"models.":[126],"terms":[128],"execution":[131],"times":[132],"tested":[134],"implementations,":[135],"SuperPoint":[136],"model":[137],"fastest,":[140],"followed":[141],"by":[142],"ORB.":[143]},"counts_by_year":[{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":5}],"updated_date":"2026-03-10T16:38:18.471706","created_date":"2019-10-25T00:00:00"}