{"id":"https://openalex.org/W3090643610","doi":"https://doi.org/10.1109/iscas45731.2020.9180818","title":"Directly Obtaining Matching Points without Keypoints for Image Stitching","display_name":"Directly Obtaining Matching Points without Keypoints for Image Stitching","publication_year":2020,"publication_date":"2020-09-29","ids":{"openalex":"https://openalex.org/W3090643610","doi":"https://doi.org/10.1109/iscas45731.2020.9180818","mag":"3090643610"},"language":"en","primary_location":{"id":"doi:10.1109/iscas45731.2020.9180818","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iscas45731.2020.9180818","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Symposium on Circuits and Systems (ISCAS)","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/A5089374633","display_name":"Yujie Huang","orcid":"https://orcid.org/0000-0001-7934-7872"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yujie Huang","raw_affiliation_strings":["State Key Laboratory of ASIC &#x0026; System, Fudan University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of ASIC &#x0026; System, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073266325","display_name":"Minge Jing","orcid":"https://orcid.org/0009-0005-0446-5600"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Minge Jing","raw_affiliation_strings":["State Key Laboratory of ASIC &#x0026; System, Fudan University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of ASIC &#x0026; System, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085004179","display_name":"Yibo Fan","orcid":"https://orcid.org/0000-0003-2523-8261"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yibo Fan","raw_affiliation_strings":["State Key Laboratory of ASIC &#x0026; System, Fudan University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of ASIC &#x0026; System, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034197769","display_name":"Xiaoyong Xue","orcid":"https://orcid.org/0000-0001-9001-4569"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoyong Xue","raw_affiliation_strings":["State Key Laboratory of ASIC &#x0026; System, Fudan University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of ASIC &#x0026; System, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100656792","display_name":"Xiaoyang Zeng","orcid":"https://orcid.org/0000-0003-3986-137X"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoyang Zeng","raw_affiliation_strings":["State Key Laboratory of ASIC &#x0026; System, Fudan University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of ASIC &#x0026; System, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I24943067"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.11341131,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"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":0.9998999834060669,"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":0.9998999834060669,"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":0.9995999932289124,"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":0.9945999979972839,"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/image-stitching","display_name":"Image stitching","score":0.9335857629776001},{"id":"https://openalex.org/keywords/scale-invariant-feature-transform","display_name":"Scale-invariant feature transform","score":0.7962877750396729},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.722841203212738},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6937246322631836},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.6457386016845703},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6435767412185669},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6098688840866089},{"id":"https://openalex.org/keywords/orb","display_name":"Orb (optics)","score":0.6091100573539734},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5605782866477966},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.5401086211204529},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5123006105422974},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.452629029750824},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4206653833389282},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.28659921884536743},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.19178611040115356}],"concepts":[{"id":"https://openalex.org/C29081049","wikidata":"https://www.wikidata.org/wiki/Q1364242","display_name":"Image stitching","level":2,"score":0.9335857629776001},{"id":"https://openalex.org/C61265191","wikidata":"https://www.wikidata.org/wiki/Q767770","display_name":"Scale-invariant feature transform","level":3,"score":0.7962877750396729},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.722841203212738},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6937246322631836},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.6457386016845703},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6435767412185669},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6098688840866089},{"id":"https://openalex.org/C108260229","wikidata":"https://www.wikidata.org/wiki/Q47023","display_name":"Orb (optics)","level":3,"score":0.6091100573539734},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5605782866477966},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.5401086211204529},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5123006105422974},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.452629029750824},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4206653833389282},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.28659921884536743},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.19178611040115356},{"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},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iscas45731.2020.9180818","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iscas45731.2020.9180818","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Symposium on Circuits and Systems (ISCAS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W1654503758","https://openalex.org/W1677409904","https://openalex.org/W1686810756","https://openalex.org/W1869500417","https://openalex.org/W1955055330","https://openalex.org/W1963246386","https://openalex.org/W1979076920","https://openalex.org/W1985320612","https://openalex.org/W2070604790","https://openalex.org/W2097117768","https://openalex.org/W2109255472","https://openalex.org/W2117228865","https://openalex.org/W2117539524","https://openalex.org/W2126060993","https://openalex.org/W2151103935","https://openalex.org/W2163605009","https://openalex.org/W2194775991","https://openalex.org/W2260746044","https://openalex.org/W2320444803","https://openalex.org/W2518764509","https://openalex.org/W2520293138","https://openalex.org/W2565639579","https://openalex.org/W2585881402","https://openalex.org/W2593948489","https://openalex.org/W2768360176","https://openalex.org/W2790280905","https://openalex.org/W2963674285","https://openalex.org/W2997095758","https://openalex.org/W3043075211","https://openalex.org/W4289665802","https://openalex.org/W6637373629","https://openalex.org/W6637400245","https://openalex.org/W6684191040","https://openalex.org/W6687483927","https://openalex.org/W6734552530"],"related_works":["https://openalex.org/W2076160147","https://openalex.org/W2388389322","https://openalex.org/W2344562887","https://openalex.org/W4388862296","https://openalex.org/W2369802839","https://openalex.org/W3103148063","https://openalex.org/W2794556651","https://openalex.org/W2266960916","https://openalex.org/W4205482147","https://openalex.org/W2763213405"],"abstract_inverted_index":{"Finding":[0],"enough":[1,18],"accurate":[2,19,159],"matching":[3,20,95,113,124,160],"points":[4,21,96,114,125,161],"is":[5,40,91,126,167],"key":[6],"for":[7],"image":[8,79],"stitching.":[9],"However,":[10],"the":[11,24,51,63,77,98,111,116,120,137,143,156,164,174,184,199],"existing":[12],"state-of-the-art":[13,175],"algorithms":[14],"fail":[15],"to":[16,42,93,109,115,139],"find":[17],"when":[22,182,198],"facing":[23,183],"challenge":[25,185],"where":[26,145,186],"detectable":[27,146,187,204],"features":[28,147,188],"are":[29,69,148,189],"not":[30,149,190],"obvious.":[31,150,191],"In":[32],"this":[33],"paper,":[34],"a":[35,86,106],"novel":[36],"algorithm":[37],"called":[38],"CNN-MP":[39,61,141,166,193],"proposed":[41,165],"directly":[43],"obtain":[44,94],"Matching":[45],"Points":[46],"between":[47,97],"two":[48,102],"images":[49,201],"using":[50],"feature":[52,87,99],"maps":[53,100],"extracted":[54],"by":[55,128,163],"Convolution":[56],"Neural":[57],"Network":[58],"(CNN)":[59],"and":[60,133,180],"skips":[62],"step":[64],"of":[65,101,122,158,173],"detecting":[66,83],"keypoints.":[67],"There":[68],"mainly":[70],"five":[71],"contributions":[72],"in":[73,142],"CNN-MP:":[74],"1)":[75],"break":[76],"conventional":[78],"stitching":[80],"steps":[81],"without":[82],"keypoints;":[84],"2)":[85],"map":[88,110],"calculation":[89],"model":[90,108],"built":[92],"images;":[103,118],"3)":[104],"establish":[105,136],"position":[107],"obtained":[112,162],"original":[117],"4)":[119],"process":[121],"obtaining":[123],"accelerated":[127],"dividing":[129],"it":[130],"into":[131],"pre-locate":[132],"fine-locate;":[134],"5)":[135],"dataset":[138],"evaluate":[140],"case":[144],"The":[151],"experimental":[152],"results":[153],"show":[154],"that":[155,172],"number":[157],"at":[168],"least":[169],"1.7":[170],"times":[171],"algorithms:":[176],"ORB,":[177],"SIFT,":[178],"LIFT":[179],"SuperPoint":[181],"Moreover,":[192],"also":[194],"achieves":[195],"good":[196],"performance":[197],"input":[200],"own":[202],"significant":[203],"features.":[205]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
