{"id":"https://openalex.org/W2120985804","doi":"https://doi.org/10.1109/icip.2007.4379800","title":"MAP Estimation of Epipolar Geometry by EM Algorithm and Local Diffusion","display_name":"MAP Estimation of Epipolar Geometry by EM Algorithm and Local Diffusion","publication_year":2007,"publication_date":"2007-01-01","ids":{"openalex":"https://openalex.org/W2120985804","doi":"https://doi.org/10.1109/icip.2007.4379800","mag":"2120985804"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2007.4379800","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2007.4379800","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2007 IEEE International Conference on Image Processing","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/A5100333961","display_name":"Wenfeng Li","orcid":"https://orcid.org/0000-0001-9491-6543"},"institutions":[{"id":"https://openalex.org/I55732556","display_name":"Arizona State University","ror":"https://ror.org/03efmqc40","country_code":"US","type":"education","lineage":["https://openalex.org/I55732556"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Wenfeng Li","raw_affiliation_strings":["Department of Computer Science & Engineering, Arizona State University, Tempe, AZ, USA","Arizona State University, Tempe,#TAB#"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science & Engineering, Arizona State University, Tempe, AZ, USA","institution_ids":["https://openalex.org/I55732556"]},{"raw_affiliation_string":"Arizona State University, Tempe,#TAB#","institution_ids":["https://openalex.org/I55732556"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5032615847","display_name":"Baoxin Li","orcid":"https://orcid.org/0000-0002-9294-4572"},"institutions":[{"id":"https://openalex.org/I55732556","display_name":"Arizona State University","ror":"https://ror.org/03efmqc40","country_code":"US","type":"education","lineage":["https://openalex.org/I55732556"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Baoxin Li","raw_affiliation_strings":["Department of Computer Science & Engineering, Arizona State University, Tempe, AZ, USA","Arizona State University, Tempe,#TAB#"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science & Engineering, Arizona State University, Tempe, AZ, USA","institution_ids":["https://openalex.org/I55732556"]},{"raw_affiliation_string":"Arizona State University, Tempe,#TAB#","institution_ids":["https://openalex.org/I55732556"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5100333961"],"corresponding_institution_ids":["https://openalex.org/I55732556"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.14822591,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":93},"biblio":{"volume":null,"issue":null,"first_page":"V ","last_page":" 201"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","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/T10531","display_name":"Advanced Vision and Imaging","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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9997000098228455,"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":0.9994999766349792,"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/epipolar-geometry","display_name":"Epipolar geometry","score":0.9896812438964844},{"id":"https://openalex.org/keywords/fundamental-matrix","display_name":"Fundamental matrix (linear differential equation)","score":0.7175394296646118},{"id":"https://openalex.org/keywords/maximum-a-posteriori-estimation","display_name":"Maximum a posteriori estimation","score":0.593214213848114},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5739943981170654},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5400311350822449},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5038866400718689},{"id":"https://openalex.org/keywords/correspondence-problem","display_name":"Correspondence problem","score":0.49659329652786255},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4874034523963928},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.48272964358329773},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.44670096039772034},{"id":"https://openalex.org/keywords/rotation","display_name":"Rotation (mathematics)","score":0.443266898393631},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.42096614837646484},{"id":"https://openalex.org/keywords/markov-random-field","display_name":"Markov random field","score":0.4123947322368622},{"id":"https://openalex.org/keywords/maximum-likelihood","display_name":"Maximum likelihood","score":0.18681520223617554},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.15847262740135193},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.15394091606140137}],"concepts":[{"id":"https://openalex.org/C23379248","wikidata":"https://www.wikidata.org/wiki/Q200904","display_name":"Epipolar geometry","level":3,"score":0.9896812438964844},{"id":"https://openalex.org/C2780427248","wikidata":"https://www.wikidata.org/wiki/Q17014996","display_name":"Fundamental matrix (linear differential equation)","level":2,"score":0.7175394296646118},{"id":"https://openalex.org/C9810830","wikidata":"https://www.wikidata.org/wiki/Q635384","display_name":"Maximum a posteriori estimation","level":3,"score":0.593214213848114},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5739943981170654},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5400311350822449},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5038866400718689},{"id":"https://openalex.org/C3004257","wikidata":"https://www.wikidata.org/wiki/Q17084606","display_name":"Correspondence problem","level":2,"score":0.49659329652786255},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4874034523963928},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.48272964358329773},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.44670096039772034},{"id":"https://openalex.org/C74050887","wikidata":"https://www.wikidata.org/wiki/Q848368","display_name":"Rotation (mathematics)","level":2,"score":0.443266898393631},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.42096614837646484},{"id":"https://openalex.org/C2778045648","wikidata":"https://www.wikidata.org/wiki/Q176827","display_name":"Markov random field","level":4,"score":0.4123947322368622},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.18681520223617554},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.15847262740135193},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.15394091606140137},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"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/icip.2007.4379800","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2007.4379800","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2007 IEEE International Conference on Image Processing","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":13,"referenced_works":["https://openalex.org/W2020999234","https://openalex.org/W2033819227","https://openalex.org/W2105192278","https://openalex.org/W2107956292","https://openalex.org/W2111308925","https://openalex.org/W2142655508","https://openalex.org/W2145713909","https://openalex.org/W2151103935","https://openalex.org/W2162387050","https://openalex.org/W2165584048","https://openalex.org/W3021282624","https://openalex.org/W6658838613","https://openalex.org/W7046283970"],"related_works":["https://openalex.org/W1533134004","https://openalex.org/W2567725087","https://openalex.org/W2394408411","https://openalex.org/W2308670625","https://openalex.org/W2120985804","https://openalex.org/W21317859","https://openalex.org/W2006151313","https://openalex.org/W3152085117","https://openalex.org/W1893582563","https://openalex.org/W1591506510"],"abstract_inverted_index":{"Finding":[0],"epipolar":[1,22,74,95],"geometry":[2,47,96],"for":[3,28,39],"two":[4],"images":[5],"is":[6,78,97],"a":[7,36,65,85],"fundamental":[8,106],"problem":[9],"in":[10,44],"computer":[11],"vision.":[12],"While":[13],"this":[14,101],"typically":[15],"relies":[16],"on":[17,84],"feature":[18,50,70],"point":[19],"correspondence,":[20],"the":[21,30,41,46,49,56,60],"constraint":[23],"can":[24,113],"also":[25],"be":[26],"used":[27],"improving":[29],"accuracy":[31],"of":[32],"correspondence.":[33],"We":[34],"propose":[35],"probabilistic":[37],"framework":[38],"estimating":[40],"epiploar":[42],"geometry,":[43],"which":[45],"and":[48,112,122],"correspondence":[51,71,77],"are":[52],"estimated":[53,73],"iteratively":[54],"at":[55],"same":[57],"time.":[58],"Using":[59],"EM":[61],"algorithm":[62],"to":[63],"maximize":[64],"posteriori,":[66],"our":[67],"approach":[68,102],"updates":[69],"with":[72,81,109],"geometry.":[75],"The":[76],"further":[79],"improved":[80],"local":[82],"diffusion":[83],"prior":[86],"Markov":[87],"Random":[88],"Field":[89],"model.":[90],"In":[91],"turn,":[92],"more":[93,104],"accurate":[94,105],"recovered.":[98],"Experiments":[99],"show":[100],"produces":[103],"matrix":[107],"compared":[108],"typical":[110],"methods":[111],"handle":[114],"some":[115],"challenging":[116],"situations":[117],"such":[118],"as":[119],"view":[120],"rotation":[121],"scale":[123],"changes.":[124]},"counts_by_year":[{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
