MotionTransformer: Transferring Neural Inertial Tracking between Domains

Changhao Chen, Yishu Miao, Chris Xiaoxuan Lu, Linhai Xie, Phil Blunsom, Andrew Markham, Niki Trigoni

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

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.
Original languageEnglish
Title of host publicationThe Thirty-Third AAAI Conference on Artificial Intelligence (AAAI-19)
PublisherAAAI Press
Pages8009 - 8016
Number of pages8
ISBN (Print)978-1-57735-809-1
DOIs
Publication statusPublished - 17 Jul 2019
EventThe Thirty-Third AAAI Conference on Artificial Intelligence - Hilton Hawaiian Village, Honolulu, Hawaii, United States
Duration: 27 Jan 20191 Feb 2019
https://aaai.org/Conferences/AAAI-19/

Publication series

NameProceedings of the AAAI Conference on Artificial Intelligence
PublisherAAAI Press
Number1
Volume33
ISSN (Print)2159-5399
ISSN (Electronic)2374-3468

Conference

ConferenceThe Thirty-Third AAAI Conference on Artificial Intelligence
Abbreviated titleAAAI 2019
CountryUnited States
CityHonolulu, Hawaii
Period27/01/191/02/19
Internet address

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