Combining Edge and One-Point RANSAC Algorithm to Estimate Visual Odometry
In recent years, classical structure from motion based SLAM has achieved significant results. Omnidirectional camera-based motion estimation has become interested researchers due to the lager field of view. This paper proposes a method to estimate the 2D motion of a vehicle and mapping by using EKF...
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| অন্যান্য লেখক: | , |
| বিন্যাস: | article |
| ভাষা: | ইংরেজি |
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2013
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| বিষয়গুলি: | |
| অনলাইন ব্যবহার করুন: | http://ridda2.utp.ac.pa/handle/123456789/5082 |
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কোনো ট্যাগ নেই, প্রথমজন হিসাবে ট্যাগ করুন!
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| _version_ | 1869652463705915392 |
|---|---|
| author | Cáceres Hernández, Danilo |
| author2 | Dung Hoang, Van Hyun Jo, Kang |
| author2_role | author author |
| author_browse | Cáceres Hernández, Danilo Dung Hoang, Van Hyun Jo, Kang |
| author_facet | Cáceres Hernández, Danilo Dung Hoang, Van Hyun Jo, Kang |
| author_role | author |
| collection | Repositorio Institucional de documento digitales de acceso abierto de la UTP |
| dc.creator.none.fl_str_mv | Cáceres Hernández, Danilo Dung Hoang, Van Hyun Jo, Kang |
| dc.date.none.fl_str_mv | 2013-07-28 2013-07-28 2018-06-27T21:04:26Z 2018-06-27T21:04:26Z 2018-06-27T21:04:26Z 2018-06-27T21:04:26Z |
| dc.format.none.fl_str_mv | application/pdf |
| dc.identifier.none.fl_str_mv | http://ridda2.utp.ac.pa/handle/123456789/5082 http://ridda2.utp.ac.pa/handle/123456789/5082 |
| dc.language.none.fl_str_mv | eng eng |
| dc.rights.none.fl_str_mv | https://creativecommons.org/licenses/by-nc-sa/4.0/ info:eu-repo/semantics/openAccess |
| dc.source.none.fl_str_mv | reponame:Repositorio Institucional de documento digitales de acceso abierto de la UTP instname:Universidad Tecnológica de Panamá instacron:U Tecnológica de Panamá |
| dc.subject.none.fl_str_mv | Omnidirectional camera edge feature matching one-point RANSAC motion and mapping Omnidirectional camera edge feature matching one-point RANSAC motion and mapping |
| dc.title.none.fl_str_mv | Combining Edge and One-Point RANSAC Algorithm to Estimate Visual Odometry |
| dc.type.none.fl_str_mv | info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
| description | In recent years, classical structure from motion based SLAM has achieved significant results. Omnidirectional camera-based motion estimation has become interested researchers due to the lager field of view. This paper proposes a method to estimate the 2D motion of a vehicle and mapping by using EKF based on edge matching and one point RANSAC. Edge matching based azimuth rotation estimation is used as pseudo prior information for EKF predicting state vector. In order to reduce requirement parameters for motion estimation and reconstruction, the vehicle moves under nonholonomic constraints car-like structured motion model assumption. The experiments were carried out using an electric vehicle with an omnidirectional camera mounted on the roof. In order to evaluate the motion estimation, the vehicle positions were compared with GPS information and superimposed onto aerial images collected by Google map API. The experimental results showed that the method based on EKF without using prior rotation information given error is about 1.9 times larger than our proposed method. |
| eu_rights_str_mv | openAccess |
| format | article |
| id | lrtest_5e646fe1f6e09bd9367c99dee245b495 |
| instacron_str | U Tecnológica de Panamá |
| institution | U Tecnológica de Panamá |
| instname_str | Universidad Tecnológica de Panamá |
| language | eng |
| network_acronym_str | lrtest |
| network_name_str | lr |
| oai_identifier_str | oai:ridda2.utp.ac.pa:123456789/5082 |
| publishDate | 2013 |
| publishDateSort | 2013 |
| reponame_str | Repositorio Institucional de documento digitales de acceso abierto de la UTP |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | https://creativecommons.org/licenses/by-nc-sa/4.0/ |
| spelling | Combining Edge and One-Point RANSAC Algorithm to Estimate Visual OdometryCáceres Hernández, DaniloDung Hoang, VanHyun Jo, KangOmnidirectional cameraedge feature matchingone-point RANSACmotion and mappingOmnidirectional cameraedge feature matchingone-point RANSACmotion and mappingIn recent years, classical structure from motion based SLAM has achieved significant results. Omnidirectional camera-based motion estimation has become interested researchers due to the lager field of view. This paper proposes a method to estimate the 2D motion of a vehicle and mapping by using EKF based on edge matching and one point RANSAC. Edge matching based azimuth rotation estimation is used as pseudo prior information for EKF predicting state vector. In order to reduce requirement parameters for motion estimation and reconstruction, the vehicle moves under nonholonomic constraints car-like structured motion model assumption. The experiments were carried out using an electric vehicle with an omnidirectional camera mounted on the roof. In order to evaluate the motion estimation, the vehicle positions were compared with GPS information and superimposed onto aerial images collected by Google map API. The experimental results showed that the method based on EKF without using prior rotation information given error is about 1.9 times larger than our proposed method.In recent years, classical structure from motion based SLAM has achieved significant results. Omnidirectional camera-based motion estimation has become interested researchers due to the lager field of view. This paper proposes a method to estimate the 2D motion of a vehicle and mapping by using EKF based on edge matching and one point RANSAC. Edge matching based azimuth rotation estimation is used as pseudo prior information for EKF predicting state vector. In order to reduce requirement parameters for motion estimation and reconstruction, the vehicle moves under nonholonomic constraints car-like structured motion model assumption. The experiments were carried out using an electric vehicle with an omnidirectional camera mounted on the roof. In order to evaluate the motion estimation, the vehicle positions were compared with GPS information and superimposed onto aerial images collected by Google map API. The experimental results showed that the method based on EKF without using prior rotation information given error is about 1.9 times larger than our proposed method.2018-06-27T21:04:26Z2018-06-27T21:04:26Z2018-06-27T21:04:26Z2018-06-27T21:04:26Z2013-07-282013-07-28info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://ridda2.utp.ac.pa/handle/123456789/5082http://ridda2.utp.ac.pa/handle/123456789/5082engenghttps://creativecommons.org/licenses/by-nc-sa/4.0/info:eu-repo/semantics/openAccessreponame:Repositorio Institucional de documento digitales de acceso abierto de la UTPinstname:Universidad Tecnológica de Panamáinstacron:U Tecnológica de Panamáoai:ridda2.utp.ac.pa:123456789/50822021-07-06T15:34:54Z |
| spellingShingle | Combining Edge and One-Point RANSAC Algorithm to Estimate Visual Odometry Cáceres Hernández, Danilo Omnidirectional camera edge feature matching one-point RANSAC motion and mapping Omnidirectional camera edge feature matching one-point RANSAC motion and mapping |
| status_str | publishedVersion |
| title | Combining Edge and One-Point RANSAC Algorithm to Estimate Visual Odometry |
| title_full | Combining Edge and One-Point RANSAC Algorithm to Estimate Visual Odometry |
| title_fullStr | Combining Edge and One-Point RANSAC Algorithm to Estimate Visual Odometry |
| title_full_unstemmed | Combining Edge and One-Point RANSAC Algorithm to Estimate Visual Odometry |
| title_short | Combining Edge and One-Point RANSAC Algorithm to Estimate Visual Odometry |
| title_sort | Combining Edge and One-Point RANSAC Algorithm to Estimate Visual Odometry |
| topic | Omnidirectional camera edge feature matching one-point RANSAC motion and mapping Omnidirectional camera edge feature matching one-point RANSAC motion and mapping |
| url | http://ridda2.utp.ac.pa/handle/123456789/5082 |