Visual odometry particle filter for improving accuracy of visual object trackers Article Swipe
This Letter proposes a novel state estimator called the visual odometry particle filter (VOPF) for improving accuracy of visual object trackers. For the VOPF, a novel visual odometry motion model that is better than the conventional constant velocity motion model is proposed. In addition, a new particle injection method to prevent sample impoverishment and the incorrect measurement detection method are proposed. Visual object tracking experiments using 30 visual object trackers demonstrate that the VOPF improves accuracy of the trackers and outperforms the conventional particle and Kalman filters using the CV motion model.
Related Topics
Concepts
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1049/el.2020.0374
- https://ietresearch.onlinelibrary.wiley.com/doi/pdfdirect/10.1049/el.2020.0374
- OA Status
- bronze
- Cited By
- 8
- References
- 13
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3034834066
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W3034834066Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1049/el.2020.0374Digital Object Identifier
- Title
-
Visual odometry particle filter for improving accuracy of visual object trackersWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2020Year of publication
- Publication date
-
2020-06-10Full publication date if available
- Authors
-
Jung Min PakList of authors in order
- Landing page
-
https://doi.org/10.1049/el.2020.0374Publisher landing page
- PDF URL
-
https://ietresearch.onlinelibrary.wiley.com/doi/pdfdirect/10.1049/el.2020.0374Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
bronzeOpen access status per OpenAlex
- OA URL
-
https://ietresearch.onlinelibrary.wiley.com/doi/pdfdirect/10.1049/el.2020.0374Direct OA link when available
- Concepts
-
Computer vision, Artificial intelligence, Particle filter, BitTorrent tracker, Odometry, Kalman filter, Computer science, Visual odometry, Video tracking, Eye tracking, Tracking (education), Estimator, Object (grammar), Mathematics, Robot, Mobile robot, Statistics, Psychology, PedagogyTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
8Total citation count in OpenAlex
- Citations by year (recent)
-
2024: 2, 2023: 4, 2022: 1, 2020: 1Per-year citation counts (last 5 years)
- References (count)
-
13Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W3034834066 |
|---|---|
| doi | https://doi.org/10.1049/el.2020.0374 |
| ids.doi | https://doi.org/10.1049/el.2020.0374 |
| ids.mag | 3034834066 |
| ids.openalex | https://openalex.org/W3034834066 |
| fwci | 0.62980391 |
| type | article |
| title | Visual odometry particle filter for improving accuracy of visual object trackers |
| awards[0].id | https://openalex.org/G6595461305 |
| awards[0].funder_id | https://openalex.org/F4320321310 |
| awards[0].display_name | |
| awards[0].funder_award_id | 2018 |
| awards[0].funder_display_name | Wonkwang University |
| biblio.issue | 17 |
| biblio.volume | 56 |
| biblio.last_page | 887 |
| biblio.first_page | 884 |
| topics[0].id | https://openalex.org/T10331 |
| topics[0].field.id | https://openalex.org/fields/17 |
| topics[0].field.display_name | Computer Science |
| topics[0].score | 0.9998999834060669 |
| topics[0].domain.id | https://openalex.org/domains/3 |
| topics[0].domain.display_name | Physical Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/1707 |
| topics[0].subfield.display_name | Computer Vision and Pattern Recognition |
| topics[0].display_name | Video Surveillance and Tracking Methods |
| 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 | 0.9994000196456909 |
| 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/T10191 |
| topics[2].field.id | https://openalex.org/fields/22 |
| topics[2].field.display_name | Engineering |
| topics[2].score | 0.986299991607666 |
| topics[2].domain.id | https://openalex.org/domains/3 |
| topics[2].domain.display_name | Physical Sciences |
| topics[2].subfield.id | https://openalex.org/subfields/2202 |
| topics[2].subfield.display_name | Aerospace Engineering |
| topics[2].display_name | Robotics and Sensor-Based Localization |
| funders[0].id | https://openalex.org/F4320321310 |
| funders[0].ror | https://ror.org/006776986 |
| funders[0].display_name | Wonkwang University |
| is_xpac | False |
| apc_list.value | 2200 |
| apc_list.currency | USD |
| apc_list.value_usd | 2200 |
| apc_paid | |
| concepts[0].id | https://openalex.org/C31972630 |
| concepts[0].level | 1 |
| concepts[0].score | 0.8060824871063232 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q844240 |
| concepts[0].display_name | Computer vision |
| concepts[1].id | https://openalex.org/C154945302 |
| concepts[1].level | 1 |
| concepts[1].score | 0.7975435853004456 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q11660 |
| concepts[1].display_name | Artificial intelligence |
| concepts[2].id | https://openalex.org/C52421305 |
| concepts[2].level | 3 |
| concepts[2].score | 0.7558724880218506 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q1151499 |
| concepts[2].display_name | Particle filter |
| concepts[3].id | https://openalex.org/C57501372 |
| concepts[3].level | 3 |
| concepts[3].score | 0.6761322617530823 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q2021268 |
| concepts[3].display_name | BitTorrent tracker |
| concepts[4].id | https://openalex.org/C49441653 |
| concepts[4].level | 4 |
| concepts[4].score | 0.6380434036254883 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q2014717 |
| concepts[4].display_name | Odometry |
| concepts[5].id | https://openalex.org/C157286648 |
| concepts[5].level | 2 |
| concepts[5].score | 0.5989022254943848 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q846780 |
| concepts[5].display_name | Kalman filter |
| concepts[6].id | https://openalex.org/C41008148 |
| concepts[6].level | 0 |
| concepts[6].score | 0.5927740931510925 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[6].display_name | Computer science |
| concepts[7].id | https://openalex.org/C5799516 |
| concepts[7].level | 3 |
| concepts[7].score | 0.5672522187232971 |
| concepts[7].wikidata | https://www.wikidata.org/wiki/Q4110915 |
| concepts[7].display_name | Visual odometry |
| concepts[8].id | https://openalex.org/C202474056 |
| concepts[8].level | 3 |
| concepts[8].score | 0.5476157665252686 |
| concepts[8].wikidata | https://www.wikidata.org/wiki/Q1931635 |
| concepts[8].display_name | Video tracking |
| concepts[9].id | https://openalex.org/C56461940 |
| concepts[9].level | 2 |
| concepts[9].score | 0.5449917912483215 |
| concepts[9].wikidata | https://www.wikidata.org/wiki/Q970687 |
| concepts[9].display_name | Eye tracking |
| concepts[10].id | https://openalex.org/C2775936607 |
| concepts[10].level | 2 |
| concepts[10].score | 0.5199329257011414 |
| concepts[10].wikidata | https://www.wikidata.org/wiki/Q466845 |
| concepts[10].display_name | Tracking (education) |
| concepts[11].id | https://openalex.org/C185429906 |
| concepts[11].level | 2 |
| concepts[11].score | 0.4203414022922516 |
| concepts[11].wikidata | https://www.wikidata.org/wiki/Q1130160 |
| concepts[11].display_name | Estimator |
| concepts[12].id | https://openalex.org/C2781238097 |
| concepts[12].level | 2 |
| concepts[12].score | 0.41725805401802063 |
| concepts[12].wikidata | https://www.wikidata.org/wiki/Q175026 |
| concepts[12].display_name | Object (grammar) |
| concepts[13].id | https://openalex.org/C33923547 |
| concepts[13].level | 0 |
| concepts[13].score | 0.2561259865760803 |
| concepts[13].wikidata | https://www.wikidata.org/wiki/Q395 |
| concepts[13].display_name | Mathematics |
| concepts[14].id | https://openalex.org/C90509273 |
| concepts[14].level | 2 |
| concepts[14].score | 0.15985891222953796 |
| concepts[14].wikidata | https://www.wikidata.org/wiki/Q11012 |
| concepts[14].display_name | Robot |
| concepts[15].id | https://openalex.org/C19966478 |
| concepts[15].level | 3 |
| concepts[15].score | 0.1458757221698761 |
| concepts[15].wikidata | https://www.wikidata.org/wiki/Q4810574 |
| concepts[15].display_name | Mobile robot |
| concepts[16].id | https://openalex.org/C105795698 |
| concepts[16].level | 1 |
| concepts[16].score | 0.0 |
| concepts[16].wikidata | https://www.wikidata.org/wiki/Q12483 |
| concepts[16].display_name | Statistics |
| concepts[17].id | https://openalex.org/C15744967 |
| concepts[17].level | 0 |
| concepts[17].score | 0.0 |
| concepts[17].wikidata | https://www.wikidata.org/wiki/Q9418 |
| concepts[17].display_name | Psychology |
| concepts[18].id | https://openalex.org/C19417346 |
| concepts[18].level | 1 |
| concepts[18].score | 0.0 |
| concepts[18].wikidata | https://www.wikidata.org/wiki/Q7922 |
| concepts[18].display_name | Pedagogy |
| keywords[0].id | https://openalex.org/keywords/computer-vision |
| keywords[0].score | 0.8060824871063232 |
| keywords[0].display_name | Computer vision |
| keywords[1].id | https://openalex.org/keywords/artificial-intelligence |
| keywords[1].score | 0.7975435853004456 |
| keywords[1].display_name | Artificial intelligence |
| keywords[2].id | https://openalex.org/keywords/particle-filter |
| keywords[2].score | 0.7558724880218506 |
| keywords[2].display_name | Particle filter |
| keywords[3].id | https://openalex.org/keywords/bittorrent-tracker |
| keywords[3].score | 0.6761322617530823 |
| keywords[3].display_name | BitTorrent tracker |
| keywords[4].id | https://openalex.org/keywords/odometry |
| keywords[4].score | 0.6380434036254883 |
| keywords[4].display_name | Odometry |
| keywords[5].id | https://openalex.org/keywords/kalman-filter |
| keywords[5].score | 0.5989022254943848 |
| keywords[5].display_name | Kalman filter |
| keywords[6].id | https://openalex.org/keywords/computer-science |
| keywords[6].score | 0.5927740931510925 |
| keywords[6].display_name | Computer science |
| keywords[7].id | https://openalex.org/keywords/visual-odometry |
| keywords[7].score | 0.5672522187232971 |
| keywords[7].display_name | Visual odometry |
| keywords[8].id | https://openalex.org/keywords/video-tracking |
| keywords[8].score | 0.5476157665252686 |
| keywords[8].display_name | Video tracking |
| keywords[9].id | https://openalex.org/keywords/eye-tracking |
| keywords[9].score | 0.5449917912483215 |
| keywords[9].display_name | Eye tracking |
| keywords[10].id | https://openalex.org/keywords/tracking |
| keywords[10].score | 0.5199329257011414 |
| keywords[10].display_name | Tracking (education) |
| keywords[11].id | https://openalex.org/keywords/estimator |
| keywords[11].score | 0.4203414022922516 |
| keywords[11].display_name | Estimator |
| keywords[12].id | https://openalex.org/keywords/object |
| keywords[12].score | 0.41725805401802063 |
| keywords[12].display_name | Object (grammar) |
| keywords[13].id | https://openalex.org/keywords/mathematics |
| keywords[13].score | 0.2561259865760803 |
| keywords[13].display_name | Mathematics |
| keywords[14].id | https://openalex.org/keywords/robot |
| keywords[14].score | 0.15985891222953796 |
| keywords[14].display_name | Robot |
| keywords[15].id | https://openalex.org/keywords/mobile-robot |
| keywords[15].score | 0.1458757221698761 |
| keywords[15].display_name | Mobile robot |
| language | en |
| locations[0].id | doi:10.1049/el.2020.0374 |
| locations[0].is_oa | True |
| locations[0].source.id | https://openalex.org/S149016011 |
| locations[0].source.issn | 0013-5194, 1350-911X |
| locations[0].source.type | journal |
| locations[0].source.is_oa | False |
| locations[0].source.issn_l | 0013-5194 |
| locations[0].source.is_core | True |
| locations[0].source.is_in_doaj | True |
| locations[0].source.display_name | Electronics Letters |
| locations[0].source.host_organization | https://openalex.org/P4310311714 |
| locations[0].source.host_organization_name | Institution of Engineering and Technology |
| locations[0].source.host_organization_lineage | https://openalex.org/P4310311714 |
| locations[0].source.host_organization_lineage_names | Institution of Engineering and Technology |
| locations[0].license | |
| locations[0].pdf_url | https://ietresearch.onlinelibrary.wiley.com/doi/pdfdirect/10.1049/el.2020.0374 |
| locations[0].version | publishedVersion |
| locations[0].raw_type | journal-article |
| locations[0].license_id | |
| locations[0].is_accepted | True |
| locations[0].is_published | True |
| locations[0].raw_source_name | Electronics Letters |
| locations[0].landing_page_url | https://doi.org/10.1049/el.2020.0374 |
| indexed_in | crossref, doaj |
| authorships[0].author.id | https://openalex.org/A5080318291 |
| authorships[0].author.orcid | https://orcid.org/0000-0002-4219-219X |
| authorships[0].author.display_name | Jung Min Pak |
| authorships[0].countries | KR |
| authorships[0].affiliations[0].institution_ids | https://openalex.org/I77079311 |
| authorships[0].affiliations[0].raw_affiliation_string | Department of Electrical Engineering, Wonkwang University, 460 Iksandae-ro, Iksan, Jeonbuk, 54538 Republic of Korea |
| authorships[0].institutions[0].id | https://openalex.org/I77079311 |
| authorships[0].institutions[0].ror | https://ror.org/006776986 |
| authorships[0].institutions[0].type | education |
| authorships[0].institutions[0].lineage | https://openalex.org/I77079311 |
| authorships[0].institutions[0].country_code | KR |
| authorships[0].institutions[0].display_name | Wonkwang University |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | J.M. Pak |
| authorships[0].is_corresponding | True |
| authorships[0].raw_affiliation_strings | Department of Electrical Engineering, Wonkwang University, 460 Iksandae-ro, Iksan, Jeonbuk, 54538 Republic of Korea |
| has_content.pdf | True |
| has_content.grobid_xml | True |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://ietresearch.onlinelibrary.wiley.com/doi/pdfdirect/10.1049/el.2020.0374 |
| open_access.oa_status | bronze |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | Visual odometry particle filter for improving accuracy of visual object trackers |
| has_fulltext | True |
| is_retracted | False |
| updated_date | 2025-11-06T03:46:38.306776 |
| primary_topic.id | https://openalex.org/T10331 |
| primary_topic.field.id | https://openalex.org/fields/17 |
| primary_topic.field.display_name | Computer Science |
| primary_topic.score | 0.9998999834060669 |
| primary_topic.domain.id | https://openalex.org/domains/3 |
| primary_topic.domain.display_name | Physical Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/1707 |
| primary_topic.subfield.display_name | Computer Vision and Pattern Recognition |
| primary_topic.display_name | Video Surveillance and Tracking Methods |
| related_works | https://openalex.org/W2979950214, https://openalex.org/W87609089, https://openalex.org/W2414561716, https://openalex.org/W3024737167, https://openalex.org/W3161199934, https://openalex.org/W2303855011, https://openalex.org/W2312326526, https://openalex.org/W2412578866, https://openalex.org/W3105866016, https://openalex.org/W4312703710 |
| cited_by_count | 8 |
| counts_by_year[0].year | 2024 |
| counts_by_year[0].cited_by_count | 2 |
| counts_by_year[1].year | 2023 |
| counts_by_year[1].cited_by_count | 4 |
| counts_by_year[2].year | 2022 |
| counts_by_year[2].cited_by_count | 1 |
| counts_by_year[3].year | 2020 |
| counts_by_year[3].cited_by_count | 1 |
| locations_count | 1 |
| best_oa_location.id | doi:10.1049/el.2020.0374 |
| best_oa_location.is_oa | True |
| best_oa_location.source.id | https://openalex.org/S149016011 |
| best_oa_location.source.issn | 0013-5194, 1350-911X |
| best_oa_location.source.type | journal |
| best_oa_location.source.is_oa | False |
| best_oa_location.source.issn_l | 0013-5194 |
| best_oa_location.source.is_core | True |
| best_oa_location.source.is_in_doaj | True |
| best_oa_location.source.display_name | Electronics Letters |
| best_oa_location.source.host_organization | https://openalex.org/P4310311714 |
| best_oa_location.source.host_organization_name | Institution of Engineering and Technology |
| best_oa_location.source.host_organization_lineage | https://openalex.org/P4310311714 |
| best_oa_location.source.host_organization_lineage_names | Institution of Engineering and Technology |
| best_oa_location.license | |
| best_oa_location.pdf_url | https://ietresearch.onlinelibrary.wiley.com/doi/pdfdirect/10.1049/el.2020.0374 |
| best_oa_location.version | publishedVersion |
| best_oa_location.raw_type | journal-article |
| best_oa_location.license_id | |
| best_oa_location.is_accepted | True |
| best_oa_location.is_published | True |
| best_oa_location.raw_source_name | Electronics Letters |
| best_oa_location.landing_page_url | https://doi.org/10.1049/el.2020.0374 |
| primary_location.id | doi:10.1049/el.2020.0374 |
| primary_location.is_oa | True |
| primary_location.source.id | https://openalex.org/S149016011 |
| primary_location.source.issn | 0013-5194, 1350-911X |
| primary_location.source.type | journal |
| primary_location.source.is_oa | False |
| primary_location.source.issn_l | 0013-5194 |
| primary_location.source.is_core | True |
| primary_location.source.is_in_doaj | True |
| primary_location.source.display_name | Electronics Letters |
| primary_location.source.host_organization | https://openalex.org/P4310311714 |
| primary_location.source.host_organization_name | Institution of Engineering and Technology |
| primary_location.source.host_organization_lineage | https://openalex.org/P4310311714 |
| primary_location.source.host_organization_lineage_names | Institution of Engineering and Technology |
| primary_location.license | |
| primary_location.pdf_url | https://ietresearch.onlinelibrary.wiley.com/doi/pdfdirect/10.1049/el.2020.0374 |
| primary_location.version | publishedVersion |
| primary_location.raw_type | journal-article |
| primary_location.license_id | |
| primary_location.is_accepted | True |
| primary_location.is_published | True |
| primary_location.raw_source_name | Electronics Letters |
| primary_location.landing_page_url | https://doi.org/10.1049/el.2020.0374 |
| publication_date | 2020-06-10 |
| publication_year | 2020 |
| referenced_works | https://openalex.org/W2126302311, https://openalex.org/W2512711598, https://openalex.org/W1029852539, https://openalex.org/W1995870198, https://openalex.org/W2107307590, https://openalex.org/W2771877920, https://openalex.org/W1187741288, https://openalex.org/W2577005688, https://openalex.org/W1642248920, https://openalex.org/W2089961441, https://openalex.org/W1568122762, https://openalex.org/W1513008779, https://openalex.org/W2913466142 |
| referenced_works_count | 13 |
| abstract_inverted_index.a | 3, 24, 44 |
| abstract_inverted_index.30 | 66 |
| abstract_inverted_index.CV | 89 |
| abstract_inverted_index.In | 42 |
| abstract_inverted_index.is | 31, 40 |
| abstract_inverted_index.of | 17, 76 |
| abstract_inverted_index.to | 49 |
| abstract_inverted_index.For | 21 |
| abstract_inverted_index.and | 53, 79, 84 |
| abstract_inverted_index.are | 59 |
| abstract_inverted_index.for | 14 |
| abstract_inverted_index.new | 45 |
| abstract_inverted_index.the | 8, 22, 34, 54, 72, 77, 81, 88 |
| abstract_inverted_index.This | 0 |
| abstract_inverted_index.VOPF | 73 |
| abstract_inverted_index.than | 33 |
| abstract_inverted_index.that | 30, 71 |
| abstract_inverted_index.VOPF, | 23 |
| abstract_inverted_index.model | 29, 39 |
| abstract_inverted_index.novel | 4, 25 |
| abstract_inverted_index.state | 5 |
| abstract_inverted_index.using | 65, 87 |
| abstract_inverted_index.(VOPF) | 13 |
| abstract_inverted_index.Kalman | 85 |
| abstract_inverted_index.Letter | 1 |
| abstract_inverted_index.Visual | 61 |
| abstract_inverted_index.better | 32 |
| abstract_inverted_index.called | 7 |
| abstract_inverted_index.filter | 12 |
| abstract_inverted_index.method | 48, 58 |
| abstract_inverted_index.model. | 91 |
| abstract_inverted_index.motion | 28, 38, 90 |
| abstract_inverted_index.object | 19, 62, 68 |
| abstract_inverted_index.sample | 51 |
| abstract_inverted_index.visual | 9, 18, 26, 67 |
| abstract_inverted_index.filters | 86 |
| abstract_inverted_index.prevent | 50 |
| abstract_inverted_index.accuracy | 16, 75 |
| abstract_inverted_index.constant | 36 |
| abstract_inverted_index.improves | 74 |
| abstract_inverted_index.odometry | 10, 27 |
| abstract_inverted_index.particle | 11, 46, 83 |
| abstract_inverted_index.proposes | 2 |
| abstract_inverted_index.trackers | 69, 78 |
| abstract_inverted_index.tracking | 63 |
| abstract_inverted_index.velocity | 37 |
| abstract_inverted_index.addition, | 43 |
| abstract_inverted_index.detection | 57 |
| abstract_inverted_index.estimator | 6 |
| abstract_inverted_index.improving | 15 |
| abstract_inverted_index.incorrect | 55 |
| abstract_inverted_index.injection | 47 |
| abstract_inverted_index.proposed. | 41, 60 |
| abstract_inverted_index.trackers. | 20 |
| abstract_inverted_index.demonstrate | 70 |
| abstract_inverted_index.experiments | 64 |
| abstract_inverted_index.measurement | 56 |
| abstract_inverted_index.outperforms | 80 |
| abstract_inverted_index.conventional | 35, 82 |
| abstract_inverted_index.impoverishment | 52 |
| cited_by_percentile_year.max | 97 |
| cited_by_percentile_year.min | 89 |
| corresponding_author_ids | https://openalex.org/A5080318291 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 1 |
| corresponding_institution_ids | https://openalex.org/I77079311 |
| citation_normalized_percentile.value | 0.69674928 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |