MotionTransformer: Transferring neural inertial tracking between domains
Inertial information processing plays a pivotal role in egomotion awareness for mobile agents, as inertial measurements are entirely egocentric and not environment dependent. However, they are affected greatly by changes in sensor placement/orientation or motion dynamics, and it is infeasible to col...
| Main Authors: | , , , , , , |
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| Format: | Conference item |
| Language: | English |
| Published: |
Association for the Advancement of Artificial Intelligence
2019
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| _version_ | 1797100191522750464 |
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| author | Chen, C Miao, Y Lu, CX Xie, L Blunsom, P Markham, A Trigoni, N |
| author_facet | Chen, C Miao, Y Lu, CX Xie, L Blunsom, P Markham, A Trigoni, N |
| author_sort | Chen, C |
| collection | OXFORD |
| description | Inertial information processing plays a pivotal role in egomotion awareness for mobile agents, as inertial measurements are entirely egocentric and not environment dependent. However, they are affected greatly by changes in sensor placement/orientation or motion dynamics, and it is infeasible to collect labelled data from every domain. To overcome the challenges of domain adaptation on long sensory sequences, we propose MotionTransformer - a novel framework that extracts domain-invariant features of raw sequences from arbitrary domains, and transforms to new domains without any paired data. Through the experiments, we demonstrate that it is able to efficiently and effectively convert the raw sequence from a new unlabelled target domain into an accurate inertial trajectory, benefiting from the motion knowledge transferred from the labelled source domain. We also conduct real-world experiments to show our framework can reconstruct physically meaningful trajectories from raw IMU measurements obtained with a standard mobile phone in various attachments. |
| first_indexed | 2024-03-07T05:34:15Z |
| format | Conference item |
| id | oxford-uuid:e3574899-98c8-40ab-a3d9-c189efd6f2bb |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-07T05:34:15Z |
| publishDate | 2019 |
| publisher | Association for the Advancement of Artificial Intelligence |
| record_format | dspace |
| spelling | oxford-uuid:e3574899-98c8-40ab-a3d9-c189efd6f2bb2022-03-27T10:08:22ZMotionTransformer: Transferring neural inertial tracking between domainsConference itemhttp://purl.org/coar/resource_type/c_5794uuid:e3574899-98c8-40ab-a3d9-c189efd6f2bbEnglishSymplectic ElementsAssociation for the Advancement of Artificial Intelligence2019Chen, CMiao, YLu, CXXie, LBlunsom, PMarkham, ATrigoni, NInertial information processing plays a pivotal role in egomotion awareness for mobile agents, as inertial measurements are entirely egocentric and not environment dependent. However, they are affected greatly by changes in sensor placement/orientation or motion dynamics, and it is infeasible to collect labelled data from every domain. To overcome the challenges of domain adaptation on long sensory sequences, we propose MotionTransformer - a novel framework that extracts domain-invariant features of raw sequences from arbitrary domains, and transforms to new domains without any paired data. Through the experiments, we demonstrate that it is able to efficiently and effectively convert the raw sequence from a new unlabelled target domain into an accurate inertial trajectory, benefiting from the motion knowledge transferred from the labelled source domain. We also conduct real-world experiments to show our framework can reconstruct physically meaningful trajectories from raw IMU measurements obtained with a standard mobile phone in various attachments. |
| spellingShingle | Chen, C Miao, Y Lu, CX Xie, L Blunsom, P Markham, A Trigoni, N MotionTransformer: Transferring neural inertial tracking between domains |
| title | MotionTransformer: Transferring neural inertial tracking between domains |
| title_full | MotionTransformer: Transferring neural inertial tracking between domains |
| title_fullStr | MotionTransformer: Transferring neural inertial tracking between domains |
| title_full_unstemmed | MotionTransformer: Transferring neural inertial tracking between domains |
| title_short | MotionTransformer: Transferring neural inertial tracking between domains |
| title_sort | motiontransformer transferring neural inertial tracking between domains |
| work_keys_str_mv | AT chenc motiontransformertransferringneuralinertialtrackingbetweendomains AT miaoy motiontransformertransferringneuralinertialtrackingbetweendomains AT lucx motiontransformertransferringneuralinertialtrackingbetweendomains AT xiel motiontransformertransferringneuralinertialtrackingbetweendomains AT blunsomp motiontransformertransferringneuralinertialtrackingbetweendomains AT markhama motiontransformertransferringneuralinertialtrackingbetweendomains AT trigonin motiontransformertransferringneuralinertialtrackingbetweendomains |