Fast and Robust Monocular Visua-Inertial Odometry Using Points and Lines Article Swipe
When the camera moves quickly and the image is blurred or the texture in the scene is missing, the Simultaneous Localization and Mapping (SLAM) algorithm based on point feature experiences difficulty tracking enough effective feature points, and the positioning accuracy and robustness are poor, and even may not work properly. For this problem, we propose a monocular visual odometry algorithm based on the point and line features and combining IMU measurement data. Based on this, an environmental-feature map with geometric information is constructed, and the IMU measurement data is incorporated to provide prior and scale information for the visual localization algorithm. Then, the initial pose estimation is obtained based on the motion estimation of the sparse image alignment, and the feature alignment is further performed to obtain the sub-pixel level feature correlation. Finally, more accurate poses and 3D landmarks are obtained by minimizing the re-projection errors of local map points and lines. The experimental results on EuRoC public datasets show that the proposed algorithm outperforms the Open Keyframe-based Visual-Inertial SLAM (OKVIS-mono) algorithm and Oriented FAST and Rotated BRIEF-SLAM (ORB-SLAM) algorithm, which demonstrates the accuracy and speed of the algorithm.
Related Topics
Concepts
Artificial intelligence
Computer vision
Simultaneous localization and mapping
Visual odometry
Odometry
Computer science
Inertial measurement unit
Robustness (evolution)
Bundle adjustment
Feature (linguistics)
Monocular
Pixel
Robot
Mobile robot
Image (mathematics)
Biochemistry
Linguistics
Gene
Chemistry
Philosophy
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/s19204545
- https://www.mdpi.com/1424-8220/19/20/4545/pdf
- OA Status
- gold
- Cited By
- 7
- References
- 46
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2980356813
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W2980356813Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3390/s19204545Digital Object Identifier
- Title
-
Fast and Robust Monocular Visua-Inertial Odometry Using Points and LinesWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2019Year of publication
- Publication date
-
2019-10-19Full publication date if available
- Authors
-
Ning Zhang, Yongjia ZhaoList of authors in order
- Landing page
-
https://doi.org/10.3390/s19204545Publisher landing page
- PDF URL
-
https://www.mdpi.com/1424-8220/19/20/4545/pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://www.mdpi.com/1424-8220/19/20/4545/pdfDirect OA link when available
- Concepts
-
Artificial intelligence, Computer vision, Simultaneous localization and mapping, Visual odometry, Odometry, Computer science, Inertial measurement unit, Robustness (evolution), Bundle adjustment, Feature (linguistics), Monocular, Pixel, Robot, Mobile robot, Image (mathematics), Biochemistry, Linguistics, Gene, Chemistry, PhilosophyTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
7Total citation count in OpenAlex
- Citations by year (recent)
-
2022: 2, 2021: 4, 2020: 1Per-year citation counts (last 5 years)
- References (count)
-
46Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W2980356813 |
|---|---|
| doi | https://doi.org/10.3390/s19204545 |
| ids.doi | https://doi.org/10.3390/s19204545 |
| ids.mag | 2980356813 |
| ids.pmid | https://pubmed.ncbi.nlm.nih.gov/31635048 |
| ids.openalex | https://openalex.org/W2980356813 |
| fwci | 2.21841787 |
| type | article |
| title | Fast and Robust Monocular Visua-Inertial Odometry Using Points and Lines |
| biblio.issue | 20 |
| biblio.volume | 19 |
| biblio.last_page | 4545 |
| biblio.first_page | 4545 |
| topics[0].id | https://openalex.org/T10191 |
| topics[0].field.id | https://openalex.org/fields/22 |
| topics[0].field.display_name | Engineering |
| topics[0].score | 1.0 |
| topics[0].domain.id | https://openalex.org/domains/3 |
| topics[0].domain.display_name | Physical Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/2202 |
| topics[0].subfield.display_name | Aerospace Engineering |
| topics[0].display_name | Robotics and Sensor-Based Localization |
| topics[1].id | https://openalex.org/T10531 |
| topics[1].field.id | https://openalex.org/fields/17 |
| topics[1].field.display_name | Computer Science |
| topics[1].score | 0.9987000226974487 |
| topics[1].domain.id | https://openalex.org/domains/3 |
| topics[1].domain.display_name | Physical Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/1707 |
| topics[1].subfield.display_name | Computer Vision and Pattern Recognition |
| topics[1].display_name | Advanced Vision and Imaging |
| topics[2].id | https://openalex.org/T11211 |
| topics[2].field.id | https://openalex.org/fields/19 |
| topics[2].field.display_name | Earth and Planetary Sciences |
| topics[2].score | 0.9984999895095825 |
| topics[2].domain.id | https://openalex.org/domains/3 |
| topics[2].domain.display_name | Physical Sciences |
| topics[2].subfield.id | https://openalex.org/subfields/1907 |
| topics[2].subfield.display_name | Geology |
| topics[2].display_name | 3D Surveying and Cultural Heritage |
| is_xpac | False |
| apc_list.value | 2400 |
| apc_list.currency | CHF |
| apc_list.value_usd | 2598 |
| apc_paid.value | 2400 |
| apc_paid.currency | CHF |
| apc_paid.value_usd | 2598 |
| concepts[0].id | https://openalex.org/C154945302 |
| concepts[0].level | 1 |
| concepts[0].score | 0.8514494895935059 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q11660 |
| concepts[0].display_name | Artificial intelligence |
| concepts[1].id | https://openalex.org/C31972630 |
| concepts[1].level | 1 |
| concepts[1].score | 0.7897058725357056 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q844240 |
| concepts[1].display_name | Computer vision |
| concepts[2].id | https://openalex.org/C86369673 |
| concepts[2].level | 4 |
| concepts[2].score | 0.7476326823234558 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q1203659 |
| concepts[2].display_name | Simultaneous localization and mapping |
| concepts[3].id | https://openalex.org/C5799516 |
| concepts[3].level | 3 |
| concepts[3].score | 0.7042028307914734 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q4110915 |
| concepts[3].display_name | Visual odometry |
| concepts[4].id | https://openalex.org/C49441653 |
| concepts[4].level | 4 |
| concepts[4].score | 0.6991515159606934 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q2014717 |
| concepts[4].display_name | Odometry |
| concepts[5].id | https://openalex.org/C41008148 |
| concepts[5].level | 0 |
| concepts[5].score | 0.63377845287323 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[5].display_name | Computer science |
| concepts[6].id | https://openalex.org/C79061980 |
| concepts[6].level | 2 |
| concepts[6].score | 0.6328150033950806 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q941680 |
| concepts[6].display_name | Inertial measurement unit |
| concepts[7].id | https://openalex.org/C63479239 |
| concepts[7].level | 3 |
| concepts[7].score | 0.6046583652496338 |
| concepts[7].wikidata | https://www.wikidata.org/wiki/Q7353546 |
| concepts[7].display_name | Robustness (evolution) |
| concepts[8].id | https://openalex.org/C179458375 |
| concepts[8].level | 3 |
| concepts[8].score | 0.5818600654602051 |
| concepts[8].wikidata | https://www.wikidata.org/wiki/Q1020763 |
| concepts[8].display_name | Bundle adjustment |
| concepts[9].id | https://openalex.org/C2776401178 |
| concepts[9].level | 2 |
| concepts[9].score | 0.5004582405090332 |
| concepts[9].wikidata | https://www.wikidata.org/wiki/Q12050496 |
| concepts[9].display_name | Feature (linguistics) |
| concepts[10].id | https://openalex.org/C65909025 |
| concepts[10].level | 2 |
| concepts[10].score | 0.49190330505371094 |
| concepts[10].wikidata | https://www.wikidata.org/wiki/Q1945033 |
| concepts[10].display_name | Monocular |
| concepts[11].id | https://openalex.org/C160633673 |
| concepts[11].level | 2 |
| concepts[11].score | 0.4167519211769104 |
| concepts[11].wikidata | https://www.wikidata.org/wiki/Q355198 |
| concepts[11].display_name | Pixel |
| concepts[12].id | https://openalex.org/C90509273 |
| concepts[12].level | 2 |
| concepts[12].score | 0.20207634568214417 |
| concepts[12].wikidata | https://www.wikidata.org/wiki/Q11012 |
| concepts[12].display_name | Robot |
| concepts[13].id | https://openalex.org/C19966478 |
| concepts[13].level | 3 |
| concepts[13].score | 0.19118696451187134 |
| concepts[13].wikidata | https://www.wikidata.org/wiki/Q4810574 |
| concepts[13].display_name | Mobile robot |
| concepts[14].id | https://openalex.org/C115961682 |
| concepts[14].level | 2 |
| concepts[14].score | 0.1781749129295349 |
| concepts[14].wikidata | https://www.wikidata.org/wiki/Q860623 |
| concepts[14].display_name | Image (mathematics) |
| concepts[15].id | https://openalex.org/C55493867 |
| concepts[15].level | 1 |
| concepts[15].score | 0.0 |
| concepts[15].wikidata | https://www.wikidata.org/wiki/Q7094 |
| concepts[15].display_name | Biochemistry |
| concepts[16].id | https://openalex.org/C41895202 |
| concepts[16].level | 1 |
| concepts[16].score | 0.0 |
| concepts[16].wikidata | https://www.wikidata.org/wiki/Q8162 |
| concepts[16].display_name | Linguistics |
| concepts[17].id | https://openalex.org/C104317684 |
| concepts[17].level | 2 |
| concepts[17].score | 0.0 |
| concepts[17].wikidata | https://www.wikidata.org/wiki/Q7187 |
| concepts[17].display_name | Gene |
| concepts[18].id | https://openalex.org/C185592680 |
| concepts[18].level | 0 |
| concepts[18].score | 0.0 |
| concepts[18].wikidata | https://www.wikidata.org/wiki/Q2329 |
| concepts[18].display_name | Chemistry |
| concepts[19].id | https://openalex.org/C138885662 |
| concepts[19].level | 0 |
| concepts[19].score | 0.0 |
| concepts[19].wikidata | https://www.wikidata.org/wiki/Q5891 |
| concepts[19].display_name | Philosophy |
| keywords[0].id | https://openalex.org/keywords/artificial-intelligence |
| keywords[0].score | 0.8514494895935059 |
| keywords[0].display_name | Artificial intelligence |
| keywords[1].id | https://openalex.org/keywords/computer-vision |
| keywords[1].score | 0.7897058725357056 |
| keywords[1].display_name | Computer vision |
| keywords[2].id | https://openalex.org/keywords/simultaneous-localization-and-mapping |
| keywords[2].score | 0.7476326823234558 |
| keywords[2].display_name | Simultaneous localization and mapping |
| keywords[3].id | https://openalex.org/keywords/visual-odometry |
| keywords[3].score | 0.7042028307914734 |
| keywords[3].display_name | Visual odometry |
| keywords[4].id | https://openalex.org/keywords/odometry |
| keywords[4].score | 0.6991515159606934 |
| keywords[4].display_name | Odometry |
| keywords[5].id | https://openalex.org/keywords/computer-science |
| keywords[5].score | 0.63377845287323 |
| keywords[5].display_name | Computer science |
| keywords[6].id | https://openalex.org/keywords/inertial-measurement-unit |
| keywords[6].score | 0.6328150033950806 |
| keywords[6].display_name | Inertial measurement unit |
| keywords[7].id | https://openalex.org/keywords/robustness |
| keywords[7].score | 0.6046583652496338 |
| keywords[7].display_name | Robustness (evolution) |
| keywords[8].id | https://openalex.org/keywords/bundle-adjustment |
| keywords[8].score | 0.5818600654602051 |
| keywords[8].display_name | Bundle adjustment |
| keywords[9].id | https://openalex.org/keywords/feature |
| keywords[9].score | 0.5004582405090332 |
| keywords[9].display_name | Feature (linguistics) |
| keywords[10].id | https://openalex.org/keywords/monocular |
| keywords[10].score | 0.49190330505371094 |
| keywords[10].display_name | Monocular |
| keywords[11].id | https://openalex.org/keywords/pixel |
| keywords[11].score | 0.4167519211769104 |
| keywords[11].display_name | Pixel |
| keywords[12].id | https://openalex.org/keywords/robot |
| keywords[12].score | 0.20207634568214417 |
| keywords[12].display_name | Robot |
| keywords[13].id | https://openalex.org/keywords/mobile-robot |
| keywords[13].score | 0.19118696451187134 |
| keywords[13].display_name | Mobile robot |
| keywords[14].id | https://openalex.org/keywords/image |
| keywords[14].score | 0.1781749129295349 |
| keywords[14].display_name | Image (mathematics) |
| language | en |
| locations[0].id | doi:10.3390/s19204545 |
| locations[0].is_oa | True |
| locations[0].source.id | https://openalex.org/S101949793 |
| locations[0].source.issn | 1424-8220 |
| locations[0].source.type | journal |
| locations[0].source.is_oa | True |
| locations[0].source.issn_l | 1424-8220 |
| locations[0].source.is_core | True |
| locations[0].source.is_in_doaj | True |
| locations[0].source.display_name | Sensors |
| locations[0].source.host_organization | https://openalex.org/P4310310987 |
| locations[0].source.host_organization_name | Multidisciplinary Digital Publishing Institute |
| locations[0].source.host_organization_lineage | https://openalex.org/P4310310987 |
| locations[0].source.host_organization_lineage_names | Multidisciplinary Digital Publishing Institute |
| locations[0].license | cc-by |
| locations[0].pdf_url | https://www.mdpi.com/1424-8220/19/20/4545/pdf |
| locations[0].version | publishedVersion |
| locations[0].raw_type | journal-article |
| locations[0].license_id | https://openalex.org/licenses/cc-by |
| locations[0].is_accepted | True |
| locations[0].is_published | True |
| locations[0].raw_source_name | Sensors |
| locations[0].landing_page_url | https://doi.org/10.3390/s19204545 |
| locations[1].id | pmid:31635048 |
| locations[1].is_oa | False |
| locations[1].source.id | https://openalex.org/S4306525036 |
| locations[1].source.issn | |
| locations[1].source.type | repository |
| locations[1].source.is_oa | False |
| locations[1].source.issn_l | |
| locations[1].source.is_core | False |
| locations[1].source.is_in_doaj | False |
| locations[1].source.display_name | PubMed |
| locations[1].source.host_organization | https://openalex.org/I1299303238 |
| locations[1].source.host_organization_name | National Institutes of Health |
| locations[1].source.host_organization_lineage | https://openalex.org/I1299303238 |
| locations[1].license | |
| locations[1].pdf_url | |
| locations[1].version | publishedVersion |
| locations[1].raw_type | |
| locations[1].license_id | |
| locations[1].is_accepted | True |
| locations[1].is_published | True |
| locations[1].raw_source_name | Sensors (Basel, Switzerland) |
| locations[1].landing_page_url | https://pubmed.ncbi.nlm.nih.gov/31635048 |
| locations[2].id | pmh:oai:doaj.org/article:a912fa4712b942f8901777fb56e09da3 |
| locations[2].is_oa | True |
| locations[2].source.id | https://openalex.org/S4306401280 |
| locations[2].source.issn | |
| locations[2].source.type | repository |
| locations[2].source.is_oa | False |
| locations[2].source.issn_l | |
| locations[2].source.is_core | False |
| locations[2].source.is_in_doaj | False |
| locations[2].source.display_name | DOAJ (DOAJ: Directory of Open Access Journals) |
| locations[2].source.host_organization | |
| locations[2].source.host_organization_name | |
| locations[2].license | cc-by-sa |
| locations[2].pdf_url | |
| locations[2].version | submittedVersion |
| locations[2].raw_type | article |
| locations[2].license_id | https://openalex.org/licenses/cc-by-sa |
| locations[2].is_accepted | False |
| locations[2].is_published | False |
| locations[2].raw_source_name | Sensors, Vol 19, Iss 20, p 4545 (2019) |
| locations[2].landing_page_url | https://doaj.org/article/a912fa4712b942f8901777fb56e09da3 |
| locations[3].id | pmh:oai:europepmc.org:5830543 |
| locations[3].is_oa | True |
| locations[3].source.id | https://openalex.org/S4306400806 |
| locations[3].source.issn | |
| locations[3].source.type | repository |
| locations[3].source.is_oa | False |
| locations[3].source.issn_l | |
| locations[3].source.is_core | False |
| locations[3].source.is_in_doaj | False |
| locations[3].source.display_name | Europe PMC (PubMed Central) |
| locations[3].source.host_organization | https://openalex.org/I1303153112 |
| locations[3].source.host_organization_name | European Bioinformatics Institute |
| locations[3].source.host_organization_lineage | https://openalex.org/I1303153112 |
| locations[3].license | other-oa |
| locations[3].pdf_url | |
| locations[3].version | submittedVersion |
| locations[3].raw_type | Text |
| locations[3].license_id | https://openalex.org/licenses/other-oa |
| locations[3].is_accepted | False |
| locations[3].is_published | False |
| locations[3].raw_source_name | |
| locations[3].landing_page_url | https://www.ncbi.nlm.nih.gov/pmc/articles/6832589 |
| locations[4].id | pmh:oai:mdpi.com:/1424-8220/19/20/4545/ |
| locations[4].is_oa | True |
| locations[4].source.id | https://openalex.org/S4306400947 |
| locations[4].source.issn | |
| locations[4].source.type | repository |
| locations[4].source.is_oa | True |
| locations[4].source.issn_l | |
| locations[4].source.is_core | False |
| locations[4].source.is_in_doaj | False |
| locations[4].source.display_name | MDPI (MDPI AG) |
| locations[4].source.host_organization | https://openalex.org/I4210097602 |
| locations[4].source.host_organization_name | Multidisciplinary Digital Publishing Institute (Switzerland) |
| locations[4].source.host_organization_lineage | https://openalex.org/I4210097602 |
| locations[4].license | cc-by |
| locations[4].pdf_url | |
| locations[4].version | submittedVersion |
| locations[4].raw_type | Text |
| locations[4].license_id | https://openalex.org/licenses/cc-by |
| locations[4].is_accepted | False |
| locations[4].is_published | False |
| locations[4].raw_source_name | Sensors |
| locations[4].landing_page_url | http://dx.doi.org/10.3390/s19204545 |
| indexed_in | crossref, doaj, pubmed |
| authorships[0].author.id | https://openalex.org/A5100404926 |
| authorships[0].author.orcid | https://orcid.org/0000-0003-4710-5830 |
| authorships[0].author.display_name | Ning Zhang |
| authorships[0].countries | CN |
| authorships[0].affiliations[0].institution_ids | https://openalex.org/I82880672 |
| authorships[0].affiliations[0].raw_affiliation_string | State Key Laboratory of Virtual Reality Technology and Systems, School of Automation Science and Eletrical Engineering, Beihang University, Beijing 100191, China |
| authorships[0].institutions[0].id | https://openalex.org/I82880672 |
| authorships[0].institutions[0].ror | https://ror.org/00wk2mp56 |
| authorships[0].institutions[0].type | education |
| authorships[0].institutions[0].lineage | https://openalex.org/I82880672 |
| authorships[0].institutions[0].country_code | CN |
| authorships[0].institutions[0].display_name | Beihang University |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Ning Zhang |
| authorships[0].is_corresponding | False |
| authorships[0].raw_affiliation_strings | State Key Laboratory of Virtual Reality Technology and Systems, School of Automation Science and Eletrical Engineering, Beihang University, Beijing 100191, China |
| authorships[1].author.id | https://openalex.org/A5082426267 |
| authorships[1].author.orcid | https://orcid.org/0000-0002-4557-9066 |
| authorships[1].author.display_name | Yongjia Zhao |
| authorships[1].countries | CN |
| authorships[1].affiliations[0].institution_ids | https://openalex.org/I82880672 |
| authorships[1].affiliations[0].raw_affiliation_string | State Key Laboratory of Virtual Reality Technology and Systems, School of Automation Science and Eletrical Engineering, Beihang University, Beijing 100191, China |
| authorships[1].institutions[0].id | https://openalex.org/I82880672 |
| authorships[1].institutions[0].ror | https://ror.org/00wk2mp56 |
| authorships[1].institutions[0].type | education |
| authorships[1].institutions[0].lineage | https://openalex.org/I82880672 |
| authorships[1].institutions[0].country_code | CN |
| authorships[1].institutions[0].display_name | Beihang University |
| authorships[1].author_position | last |
| authorships[1].raw_author_name | Yongjia Zhao |
| authorships[1].is_corresponding | True |
| authorships[1].raw_affiliation_strings | State Key Laboratory of Virtual Reality Technology and Systems, School of Automation Science and Eletrical Engineering, Beihang University, Beijing 100191, China |
| has_content.pdf | True |
| has_content.grobid_xml | True |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://www.mdpi.com/1424-8220/19/20/4545/pdf |
| open_access.oa_status | gold |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | Fast and Robust Monocular Visua-Inertial Odometry Using Points and Lines |
| has_fulltext | True |
| is_retracted | False |
| updated_date | 2025-11-06T03:46:38.306776 |
| primary_topic.id | https://openalex.org/T10191 |
| primary_topic.field.id | https://openalex.org/fields/22 |
| primary_topic.field.display_name | Engineering |
| primary_topic.score | 1.0 |
| primary_topic.domain.id | https://openalex.org/domains/3 |
| primary_topic.domain.display_name | Physical Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/2202 |
| primary_topic.subfield.display_name | Aerospace Engineering |
| primary_topic.display_name | Robotics and Sensor-Based Localization |
| related_works | https://openalex.org/W2979950214, https://openalex.org/W87609089, https://openalex.org/W3024737167, https://openalex.org/W2414561716, https://openalex.org/W2084446318, https://openalex.org/W3161199934, https://openalex.org/W2303855011, https://openalex.org/W2981103992, https://openalex.org/W2312326526, https://openalex.org/W3105866016 |
| cited_by_count | 7 |
| counts_by_year[0].year | 2022 |
| counts_by_year[0].cited_by_count | 2 |
| counts_by_year[1].year | 2021 |
| counts_by_year[1].cited_by_count | 4 |
| counts_by_year[2].year | 2020 |
| counts_by_year[2].cited_by_count | 1 |
| locations_count | 5 |
| best_oa_location.id | doi:10.3390/s19204545 |
| best_oa_location.is_oa | True |
| best_oa_location.source.id | https://openalex.org/S101949793 |
| best_oa_location.source.issn | 1424-8220 |
| best_oa_location.source.type | journal |
| best_oa_location.source.is_oa | True |
| best_oa_location.source.issn_l | 1424-8220 |
| best_oa_location.source.is_core | True |
| best_oa_location.source.is_in_doaj | True |
| best_oa_location.source.display_name | Sensors |
| best_oa_location.source.host_organization | https://openalex.org/P4310310987 |
| best_oa_location.source.host_organization_name | Multidisciplinary Digital Publishing Institute |
| best_oa_location.source.host_organization_lineage | https://openalex.org/P4310310987 |
| best_oa_location.source.host_organization_lineage_names | Multidisciplinary Digital Publishing Institute |
| best_oa_location.license | cc-by |
| best_oa_location.pdf_url | https://www.mdpi.com/1424-8220/19/20/4545/pdf |
| best_oa_location.version | publishedVersion |
| best_oa_location.raw_type | journal-article |
| best_oa_location.license_id | https://openalex.org/licenses/cc-by |
| best_oa_location.is_accepted | True |
| best_oa_location.is_published | True |
| best_oa_location.raw_source_name | Sensors |
| best_oa_location.landing_page_url | https://doi.org/10.3390/s19204545 |
| primary_location.id | doi:10.3390/s19204545 |
| primary_location.is_oa | True |
| primary_location.source.id | https://openalex.org/S101949793 |
| primary_location.source.issn | 1424-8220 |
| primary_location.source.type | journal |
| primary_location.source.is_oa | True |
| primary_location.source.issn_l | 1424-8220 |
| primary_location.source.is_core | True |
| primary_location.source.is_in_doaj | True |
| primary_location.source.display_name | Sensors |
| primary_location.source.host_organization | https://openalex.org/P4310310987 |
| primary_location.source.host_organization_name | Multidisciplinary Digital Publishing Institute |
| primary_location.source.host_organization_lineage | https://openalex.org/P4310310987 |
| primary_location.source.host_organization_lineage_names | Multidisciplinary Digital Publishing Institute |
| primary_location.license | cc-by |
| primary_location.pdf_url | https://www.mdpi.com/1424-8220/19/20/4545/pdf |
| primary_location.version | publishedVersion |
| primary_location.raw_type | journal-article |
| primary_location.license_id | https://openalex.org/licenses/cc-by |
| primary_location.is_accepted | True |
| primary_location.is_published | True |
| primary_location.raw_source_name | Sensors |
| primary_location.landing_page_url | https://doi.org/10.3390/s19204545 |
| publication_date | 2019-10-19 |
| publication_year | 2019 |
| referenced_works | https://openalex.org/W1979266466, https://openalex.org/W2127578024, https://openalex.org/W2773097480, https://openalex.org/W2732510496, https://openalex.org/W2904353685, https://openalex.org/W2180280991, https://openalex.org/W2152671441, https://openalex.org/W2151290401, https://openalex.org/W1612997784, https://openalex.org/W2108134361, https://openalex.org/W612478963, https://openalex.org/W2474281075, https://openalex.org/W1970504153, https://openalex.org/W2064451896, https://openalex.org/W2005750530, https://openalex.org/W2119605622, https://openalex.org/W2117228865, https://openalex.org/W2160072137, https://openalex.org/W2185786809, https://openalex.org/W2733709179, https://openalex.org/W2055401374, https://openalex.org/W1981778017, https://openalex.org/W2411918187, https://openalex.org/W2738596250, https://openalex.org/W2059302785, https://openalex.org/W2962754043, https://openalex.org/W2127752689, https://openalex.org/W2745859992, https://openalex.org/W2091790851, https://openalex.org/W2538522345, https://openalex.org/W2942369749, https://openalex.org/W2173066840, https://openalex.org/W2796916234, https://openalex.org/W1998058414, https://openalex.org/W2773447888, https://openalex.org/W2342437324, https://openalex.org/W1991544872, https://openalex.org/W2482726005, https://openalex.org/W2035379092, https://openalex.org/W2396274919, https://openalex.org/W2008849352, https://openalex.org/W2963200201, https://openalex.org/W3125449081, https://openalex.org/W2146881125, https://openalex.org/W3103648783, https://openalex.org/W2617734768 |
| referenced_works_count | 46 |
| abstract_inverted_index.a | 55 |
| abstract_inverted_index.3D | 137 |
| abstract_inverted_index.an | 75 |
| abstract_inverted_index.by | 141 |
| abstract_inverted_index.in | 13 |
| abstract_inverted_index.is | 8, 16, 81, 88, 106, 122 |
| abstract_inverted_index.of | 113, 146, 186 |
| abstract_inverted_index.on | 26, 61, 73, 109, 155 |
| abstract_inverted_index.or | 10 |
| abstract_inverted_index.to | 90, 125 |
| abstract_inverted_index.we | 53 |
| abstract_inverted_index.For | 50 |
| abstract_inverted_index.IMU | 69, 85 |
| abstract_inverted_index.The | 152 |
| abstract_inverted_index.and | 5, 21, 36, 40, 44, 64, 67, 83, 93, 118, 136, 150, 172, 175, 184 |
| abstract_inverted_index.are | 42, 139 |
| abstract_inverted_index.for | 96 |
| abstract_inverted_index.map | 77, 148 |
| abstract_inverted_index.may | 46 |
| abstract_inverted_index.not | 47 |
| abstract_inverted_index.the | 1, 6, 11, 14, 18, 37, 62, 84, 97, 102, 110, 114, 119, 127, 143, 161, 165, 182, 187 |
| abstract_inverted_index.FAST | 174 |
| abstract_inverted_index.Open | 166 |
| abstract_inverted_index.SLAM | 169 |
| abstract_inverted_index.When | 0 |
| abstract_inverted_index.data | 87 |
| abstract_inverted_index.even | 45 |
| abstract_inverted_index.line | 65 |
| abstract_inverted_index.more | 133 |
| abstract_inverted_index.pose | 104 |
| abstract_inverted_index.show | 159 |
| abstract_inverted_index.that | 160 |
| abstract_inverted_index.this | 51 |
| abstract_inverted_index.with | 78 |
| abstract_inverted_index.work | 48 |
| abstract_inverted_index.Based | 72 |
| abstract_inverted_index.EuRoC | 156 |
| abstract_inverted_index.Then, | 101 |
| abstract_inverted_index.based | 25, 60, 108 |
| abstract_inverted_index.data. | 71 |
| abstract_inverted_index.image | 7, 116 |
| abstract_inverted_index.level | 129 |
| abstract_inverted_index.local | 147 |
| abstract_inverted_index.moves | 3 |
| abstract_inverted_index.point | 27, 63 |
| abstract_inverted_index.poor, | 43 |
| abstract_inverted_index.poses | 135 |
| abstract_inverted_index.prior | 92 |
| abstract_inverted_index.scale | 94 |
| abstract_inverted_index.scene | 15 |
| abstract_inverted_index.speed | 185 |
| abstract_inverted_index.this, | 74 |
| abstract_inverted_index.which | 180 |
| abstract_inverted_index.(SLAM) | 23 |
| abstract_inverted_index.camera | 2 |
| abstract_inverted_index.enough | 32 |
| abstract_inverted_index.errors | 145 |
| abstract_inverted_index.lines. | 151 |
| abstract_inverted_index.motion | 111 |
| abstract_inverted_index.obtain | 126 |
| abstract_inverted_index.points | 149 |
| abstract_inverted_index.public | 157 |
| abstract_inverted_index.sparse | 115 |
| abstract_inverted_index.visual | 57, 98 |
| abstract_inverted_index.Mapping | 22 |
| abstract_inverted_index.Rotated | 176 |
| abstract_inverted_index.blurred | 9 |
| abstract_inverted_index.feature | 28, 34, 120, 130 |
| abstract_inverted_index.further | 123 |
| abstract_inverted_index.initial | 103 |
| abstract_inverted_index.points, | 35 |
| abstract_inverted_index.propose | 54 |
| abstract_inverted_index.provide | 91 |
| abstract_inverted_index.quickly | 4 |
| abstract_inverted_index.results | 154 |
| abstract_inverted_index.texture | 12 |
| abstract_inverted_index.Finally, | 132 |
| abstract_inverted_index.Oriented | 173 |
| abstract_inverted_index.accuracy | 39, 183 |
| abstract_inverted_index.accurate | 134 |
| abstract_inverted_index.datasets | 158 |
| abstract_inverted_index.features | 66 |
| abstract_inverted_index.missing, | 17 |
| abstract_inverted_index.obtained | 107, 140 |
| abstract_inverted_index.odometry | 58 |
| abstract_inverted_index.problem, | 52 |
| abstract_inverted_index.proposed | 162 |
| abstract_inverted_index.tracking | 31 |
| abstract_inverted_index.algorithm | 24, 59, 163, 171 |
| abstract_inverted_index.alignment | 121 |
| abstract_inverted_index.combining | 68 |
| abstract_inverted_index.effective | 33 |
| abstract_inverted_index.geometric | 79 |
| abstract_inverted_index.landmarks | 138 |
| abstract_inverted_index.monocular | 56 |
| abstract_inverted_index.performed | 124 |
| abstract_inverted_index.properly. | 49 |
| abstract_inverted_index.sub-pixel | 128 |
| abstract_inverted_index.(ORB-SLAM) | 178 |
| abstract_inverted_index.BRIEF-SLAM | 177 |
| abstract_inverted_index.algorithm, | 179 |
| abstract_inverted_index.algorithm. | 100, 188 |
| abstract_inverted_index.alignment, | 117 |
| abstract_inverted_index.difficulty | 30 |
| abstract_inverted_index.estimation | 105, 112 |
| abstract_inverted_index.minimizing | 142 |
| abstract_inverted_index.robustness | 41 |
| abstract_inverted_index.experiences | 29 |
| abstract_inverted_index.information | 80, 95 |
| abstract_inverted_index.measurement | 70, 86 |
| abstract_inverted_index.outperforms | 164 |
| abstract_inverted_index.positioning | 38 |
| abstract_inverted_index.(OKVIS-mono) | 170 |
| abstract_inverted_index.Localization | 20 |
| abstract_inverted_index.Simultaneous | 19 |
| abstract_inverted_index.constructed, | 82 |
| abstract_inverted_index.correlation. | 131 |
| abstract_inverted_index.demonstrates | 181 |
| abstract_inverted_index.experimental | 153 |
| abstract_inverted_index.incorporated | 89 |
| abstract_inverted_index.localization | 99 |
| abstract_inverted_index.re-projection | 144 |
| abstract_inverted_index.Keyframe-based | 167 |
| abstract_inverted_index.Visual-Inertial | 168 |
| abstract_inverted_index.environmental-feature | 76 |
| cited_by_percentile_year.max | 97 |
| cited_by_percentile_year.min | 89 |
| corresponding_author_ids | https://openalex.org/A5082426267 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 2 |
| corresponding_institution_ids | https://openalex.org/I82880672 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/1 |
| sustainable_development_goals[0].score | 0.5199999809265137 |
| sustainable_development_goals[0].display_name | No poverty |
| citation_normalized_percentile.value | 0.9073541 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |