{"id":"https://openalex.org/W4405785006","doi":"https://doi.org/10.1109/iros58592.2024.10802351","title":"DeepBHMR: Learning Bidirectional Hybrid Mixture Models for Generalized Rigid Point Set Registration","display_name":"DeepBHMR: Learning Bidirectional Hybrid Mixture Models for Generalized Rigid Point Set Registration","publication_year":2024,"publication_date":"2024-10-14","ids":{"openalex":"https://openalex.org/W4405785006","doi":"https://doi.org/10.1109/iros58592.2024.10802351"},"language":"en","primary_location":{"id":"doi:10.1109/iros58592.2024.10802351","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros58592.2024.10802351","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 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/A5040071840","display_name":"Zhe Min","orcid":"https://orcid.org/0000-0002-8903-1561"},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhe Min","raw_affiliation_strings":["Shandong University,School of Control Science and Engineering,China"],"affiliations":[{"raw_affiliation_string":"Shandong University,School of Control Science and Engineering,China","institution_ids":["https://openalex.org/I154099455"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027367137","display_name":"Zhengyan Zhang","orcid":"https://orcid.org/0000-0002-4906-4481"},"institutions":[{"id":"https://openalex.org/I14243506","display_name":"Hong Kong Polytechnic University","ror":"https://ror.org/0030zas98","country_code":"HK","type":"education","lineage":["https://openalex.org/I14243506"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Zhengyan Zhang","raw_affiliation_strings":["The Hong Kong Polytechnic University,Department of Aeronautical and Aviation Engineering"],"affiliations":[{"raw_affiliation_string":"The Hong Kong Polytechnic University,Department of Aeronautical and Aviation Engineering","institution_ids":["https://openalex.org/I14243506"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101541870","display_name":"Ang Zhang","orcid":"https://orcid.org/0000-0002-0749-5822"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ang Zhang","raw_affiliation_strings":["Perception and AI Technologies Ltd,Yuanhua Robotics,Shenzhen,China"],"affiliations":[{"raw_affiliation_string":"Perception and AI Technologies Ltd,Yuanhua Robotics,Shenzhen,China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101645277","display_name":"Rui Song","orcid":"https://orcid.org/0000-0002-4119-4433"},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rui Song","raw_affiliation_strings":["Shandong University,School of Control Science and Engineering,China"],"affiliations":[{"raw_affiliation_string":"Shandong University,School of Control Science and Engineering,China","institution_ids":["https://openalex.org/I154099455"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100724411","display_name":"Yibin Li","orcid":"https://orcid.org/0000-0002-5906-5074"},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yibin Li","raw_affiliation_strings":["Shandong University,School of Control Science and Engineering,China"],"affiliations":[{"raw_affiliation_string":"Shandong University,School of Control Science and Engineering,China","institution_ids":["https://openalex.org/I154099455"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5021531143","display_name":"Max Q.\u2010H. Meng","orcid":"https://orcid.org/0000-0002-5255-5898"},"institutions":[{"id":"https://openalex.org/I3045169105","display_name":"Southern University of Science and Technology","ror":"https://ror.org/049tv2d57","country_code":"CN","type":"education","lineage":["https://openalex.org/I3045169105"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Max Q.-H. Meng","raw_affiliation_strings":["Southern University of Science and Technology,Department of Electronic and Electrical Engineering,Shenzhen,China"],"affiliations":[{"raw_affiliation_string":"Southern University of Science and Technology,Department of Electronic and Electrical Engineering,Shenzhen,China","institution_ids":["https://openalex.org/I3045169105"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5040071840"],"corresponding_institution_ids":["https://openalex.org/I154099455"],"apc_list":null,"apc_paid":null,"fwci":0.7274,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.78123406,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"13160","last_page":"13167"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.991599977016449,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.991599977016449,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/point","display_name":"Point (geometry)","score":0.6420816779136658},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.611931324005127},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5731316208839417},{"id":"https://openalex.org/keywords/point-set-registration","display_name":"Point set registration","score":0.4623836874961853},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.43644002079963684},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.41542840003967285},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.21059221029281616},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.15361812710762024}],"concepts":[{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.6420816779136658},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.611931324005127},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5731316208839417},{"id":"https://openalex.org/C200336642","wikidata":"https://www.wikidata.org/wiki/Q15058706","display_name":"Point set registration","level":3,"score":0.4623836874961853},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43644002079963684},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.41542840003967285},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.21059221029281616},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.15361812710762024},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iros58592.2024.10802351","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros58592.2024.10802351","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320310075","display_name":"Jinan Science and Technology Bureau","ror":"https://ror.org/016p59286"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335581","display_name":"Young Scientists Fund","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W1984905474","https://openalex.org/W2049981393","https://openalex.org/W2134236847","https://openalex.org/W2201863444","https://openalex.org/W2990613095","https://openalex.org/W3005226310","https://openalex.org/W3034295752","https://openalex.org/W3096538374","https://openalex.org/W3134976640","https://openalex.org/W3177280664","https://openalex.org/W3205871067","https://openalex.org/W3214555988","https://openalex.org/W4220713653","https://openalex.org/W4225983328","https://openalex.org/W4285189169","https://openalex.org/W4309334867","https://openalex.org/W4312516208","https://openalex.org/W4319300821","https://openalex.org/W4364322751","https://openalex.org/W4383108275","https://openalex.org/W4386629177","https://openalex.org/W4387623782","https://openalex.org/W4399167797","https://openalex.org/W6682124274","https://openalex.org/W6856927293"],"related_works":["https://openalex.org/W2772917594","https://openalex.org/W2036807459","https://openalex.org/W2058170566","https://openalex.org/W2755342338","https://openalex.org/W2166024367","https://openalex.org/W3116076068","https://openalex.org/W2229312674","https://openalex.org/W2951359407","https://openalex.org/W2079911747","https://openalex.org/W1969923398"],"abstract_inverted_index":{"In":[0,147],"this":[1],"paper,":[2],"we":[3],"introduce":[4],"a":[5,40],"novel":[6],"normal-assisted":[7],"learning-based":[8],"rigid":[9],"registration":[10,38,142],"approach,":[11],"i.e.,":[12],"Deep":[13],"Bi-directional":[14],"Hybrid":[15,79],"Mixture":[16,80],"Registration":[17],"(DeepBHMR).":[18],"Our":[19],"approach":[20],"utilises":[21],"helpful":[22],"normal":[23,74,222],"vectors":[24,223],"explicitly":[25],"in":[26,39,46,180],"both":[27,47],"correspondence":[28,57,62],"and":[29,32,73,106,117,128,132,156,165,185,224,238],"transformation":[30,99,178,237],"stages":[31],"formulates":[33],"the":[34,56,61,84,90,98,103,107,111,140,148,153,176,181,189,200,203,217,225,232],"optimization":[35],"objective":[36],"of":[37,52,78,150,183,220,235],"bi-directional":[41],"way":[42],"that":[43,59,93,101,137],"considers":[44],"noise":[45],"point":[48,69,87],"sets.":[49],"DeepBHMR":[50,120,138,228],"consists":[51],"three":[53],"modules:":[54],"(1)":[55],"network":[58],"estimates":[60],"probability":[63],"relating":[64],"points":[65],"within":[66],"one":[67],"generalized":[68,86],"set":[70],"(i.e.,":[71,163,170,179],"positional":[72],"vectors)":[75],"with":[76],"components":[77],"Models":[81],"(HMMs)":[82],"representing":[83],"other":[85],"set;":[88],"(2)":[89],"posterior":[91],"module":[92,100],"computes":[94,102],"HMMs":[95,118],"parameters;":[96],"(3)":[97],"rotation":[104,155],"matrix":[105],"translation":[108,157],"vector":[109],"given":[110],"estimated":[112],"generalized-point":[113],"to":[114,210],"hybrid-distribution":[115],"correspondences":[116],"parameters.":[119],"has":[121],"been":[122],"validated":[123,216],"on":[124],"291":[125],"human":[126],"femur":[127,151,208],"260":[129],"hip":[130,211],"models,":[131],"extensive":[133],"experimental":[134],"results":[135,201],"demonstrate":[136,202],"outperforms":[139],"state-of-the-art":[141],"methods":[143],"(p-value":[144],"<":[145],"0.01).":[146],"circumstance":[149],"bones,":[152],"mean":[154,190],"error":[158],"values":[159,192],"are":[160,243],"around":[161],"1\u00b0":[162],"1.01\u00b0)":[164],"less":[166],"than":[167],"1":[168],"mm":[169,195],"0.36mm),":[171],"respectively.":[172],"Furthermore,":[173],"even":[174],"under":[175],"large":[177,236],"range":[182],"[0,180]\u00b0":[184],"[0,":[186],"100]":[187],"mm),":[188],"RMSE":[191],"being":[193],"3.05":[194],"is":[196],"still":[197],"satisfactory.":[198],"Additionally,":[199],"DeepBHMR\u2019s":[204],"favorable":[205],"generalizability":[206],"from":[207],"shapes":[209],"shapes.":[212],"We":[213],"have":[214],"carefully":[215],"significant":[218],"benefits":[219],"incorporating":[221],"bidirectional":[226],"mechanism.":[227],"can":[229],"successfully":[230],"handle":[231],"challenging":[233],"scenario":[234],"partial":[239],"registration.":[240],"The":[241],"codes":[242],"available":[244],"at":[245],"https://github.com/zzyrobot/DeepBHMR.git.":[246]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
