{"id":"https://openalex.org/W7134932663","doi":"https://doi.org/10.48550/arxiv.2603.09653","title":"OTPL-VIO: Robust Visual-Inertial Odometry with Optimal Transport Line Association and Adaptive Uncertainty","display_name":"OTPL-VIO: Robust Visual-Inertial Odometry with Optimal Transport Line Association and Adaptive Uncertainty","publication_year":2026,"publication_date":"2026-03-10","ids":{"openalex":"https://openalex.org/W7134932663","doi":"https://doi.org/10.48550/arxiv.2603.09653"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.09653","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.09653","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.09653","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5125507610","display_name":"Zikun Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Zikun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128755777","display_name":"Wentao Zhao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhao, Wentao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059918186","display_name":"Yihe Niu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Niu, Yihe","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128767631","display_name":"Tianchen Deng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Deng, Tianchen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5128703379","display_name":"Jingchuan Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Jingchuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9097999930381775,"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":0.9097999930381775,"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":0.06319999694824219,"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":0.004699999932199717,"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/odometry","display_name":"Odometry","score":0.8468999862670898},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.7111999988555908},{"id":"https://openalex.org/keywords/weighting","display_name":"Weighting","score":0.5911999940872192},{"id":"https://openalex.org/keywords/line","display_name":"Line (geometry)","score":0.5049999952316284},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5004000067710876},{"id":"https://openalex.org/keywords/line-segment","display_name":"Line segment","score":0.4377000033855438},{"id":"https://openalex.org/keywords/pooling","display_name":"Pooling","score":0.43549999594688416},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.4246000051498413},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.39879998564720154},{"id":"https://openalex.org/keywords/simultaneous-localization-and-mapping","display_name":"Simultaneous localization and mapping","score":0.3986999988555908}],"concepts":[{"id":"https://openalex.org/C49441653","wikidata":"https://www.wikidata.org/wiki/Q2014717","display_name":"Odometry","level":4,"score":0.8468999862670898},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7111999988555908},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6758999824523926},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6644999980926514},{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.5911999940872192},{"id":"https://openalex.org/C198352243","wikidata":"https://www.wikidata.org/wiki/Q37105","display_name":"Line (geometry)","level":2,"score":0.5049999952316284},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5004000067710876},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.47519999742507935},{"id":"https://openalex.org/C182124507","wikidata":"https://www.wikidata.org/wiki/Q166154","display_name":"Line segment","level":2,"score":0.4377000033855438},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.43549999594688416},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.4246000051498413},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.39879998564720154},{"id":"https://openalex.org/C86369673","wikidata":"https://www.wikidata.org/wiki/Q1203659","display_name":"Simultaneous localization and mapping","level":4,"score":0.3986999988555908},{"id":"https://openalex.org/C5799516","wikidata":"https://www.wikidata.org/wiki/Q4110915","display_name":"Visual odometry","level":3,"score":0.35260000824928284},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.349700003862381},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.323199987411499},{"id":"https://openalex.org/C70136482","wikidata":"https://www.wikidata.org/wiki/Q13583781","display_name":"A-weighting","level":3,"score":0.3199999928474426},{"id":"https://openalex.org/C23379248","wikidata":"https://www.wikidata.org/wiki/Q200904","display_name":"Epipolar geometry","level":3,"score":0.3125999867916107},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.3018999993801117},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3018999993801117},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.30149999260902405},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.30059999227523804},{"id":"https://openalex.org/C2779188883","wikidata":"https://www.wikidata.org/wiki/Q82446","display_name":"Global Map","level":3,"score":0.3003999888896942},{"id":"https://openalex.org/C42747912","wikidata":"https://www.wikidata.org/wiki/Q1048447","display_name":"Multiplicative function","level":2,"score":0.2912999987602234},{"id":"https://openalex.org/C2983325608","wikidata":"https://www.wikidata.org/wiki/Q17084606","display_name":"Data association","level":3,"score":0.29019999504089355},{"id":"https://openalex.org/C157286648","wikidata":"https://www.wikidata.org/wiki/Q846780","display_name":"Kalman filter","level":2,"score":0.28870001435279846},{"id":"https://openalex.org/C142853389","wikidata":"https://www.wikidata.org/wiki/Q744778","display_name":"Association (psychology)","level":2,"score":0.28450000286102295},{"id":"https://openalex.org/C18015164","wikidata":"https://www.wikidata.org/wiki/Q6935000","display_name":"Multiplicative noise","level":5,"score":0.2621000111103058},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.2590000033378601},{"id":"https://openalex.org/C55166926","wikidata":"https://www.wikidata.org/wiki/Q2892946","display_name":"Oracle","level":2,"score":0.2567000091075897},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.2547000050544739},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.25380000472068787}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.09653","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.09653","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.09653","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.09653","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Robust":[0],"stereo":[1,64],"visual-inertial":[2],"odometry":[3],"(VIO)":[4],"remains":[5],"challenging":[6],"in":[7,68,145],"low-texture":[8,146],"scenes":[9],"and":[10,20,26,55,78,93,101,106,123,139,147,153],"under":[11,90],"abrupt":[12],"illumination":[13],"changes,":[14],"where":[15],"point":[16,51],"features":[17],"become":[18],"sparse":[19],"unstable,":[21],"leading":[22],"to":[23,58,127],"ambiguous":[24],"association":[25],"under-constrained":[27],"estimation.":[28],"Line":[29],"structures":[30],"offer":[31],"complementary":[32],"geometric":[33],"cues,":[34],"yet":[35],"many":[36],"efficient":[37],"point-line":[38,65],"systems":[39],"still":[40],"rely":[41],"on":[42,137],"point-guided":[43],"line":[44,70,120,132],"association,":[45],"which":[46,69],"can":[47],"break":[48],"down":[49],"when":[50],"support":[52],"is":[53,99,102],"weak":[54],"may":[56],"lead":[57],"biased":[59],"constraints.":[60],"We":[61],"present":[62],"a":[63],"VIO":[66],"system":[67],"segments":[71],"are":[72],"equipped":[73],"with":[74,142],"dedicated":[75],"deep":[76],"descriptors":[77],"matched":[79],"using":[80],"an":[81],"entropy-regularized":[82],"optimal":[83],"transport":[84],"formulation,":[85],"enabling":[86],"globally":[87],"consistent":[88],"correspondences":[89],"ambiguity,":[91],"outliers,":[92],"partial":[94],"observations.":[95],"The":[96],"proposed":[97],"descriptor":[98],"training-free":[100],"computed":[103],"by":[104],"sampling":[105],"pooling":[107],"network":[108],"feature":[109],"maps.":[110],"To":[111],"improve":[112],"estimation":[113],"stability,":[114],"we":[115],"analyze":[116],"the":[117,129],"impact":[118],"of":[119,131],"measurement":[121],"noise":[122],"introduce":[124],"reliability-adaptive":[125],"weighting":[126],"regulate":[128],"influence":[130],"constraints":[133],"during":[134],"optimization.":[135],"Experiments":[136],"EuRoC":[138],"UMA-VI,":[140],"together":[141],"real-world":[143],"deployments":[144],"illumination-challenging":[148],"environments,":[149],"demonstrate":[150],"improved":[151],"accuracy":[152],"robustness":[154],"over":[155],"representative":[156],"baselines":[157],"while":[158],"maintaining":[159],"real-time":[160],"performance.":[161]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-03-12T00:00:00"}
