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Accelerometer dense trajectories for activity recognition and people identification
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Leyva, Roberto, Santos, Geise, Rocha, Anderson, Sanchez Silva, Victor and Li, Chang-Tsun (2018) Accelerometer dense trajectories for activity recognition and people identification. In: 2019 7th International Workshop on Biometrics and Forensics (IWBF), Cancun, Mexico, Mexico, 2-3 May 2019 ISBN 9781728106229. doi:10.1109/IWBF.2019.8739218
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Official URL: http://dx.doi.org/10.1109/IWBF.2019.8739218
Abstract
This paper addresses the problem of activity recog- nition and people identification using accelerometer signals ac- quired by personal devices. Specifically, we propose a framework based on a Deep Neural Network that employs an efficient dense trajectory encoding to compute features. These Accelerometer Dense Trajectory (ADT) features, which are similar to those used for action recognition in the spatio-temporal domain of video data, densely map the accelerometer signals into three- dimensional normalised positions. To deal with the unordered nature and dimensional variation of trajectories associated with the classes, the proposed framework employs Fisher Vectors as a high order representation of the extracted features. We evaluate the proposed ADT features and framework on the Sphere2016 Challenge and WISDM datasets for activity recognition. For people identification, we employ the RecodGait dataset. For these two significantly different classification tasks, the perfor- mance evaluation results confirm the high descriptiveness of the proposed ADT features and the effectiveness of the proposed framework.
Item Type: | Conference Item (Paper) | ||||||
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Subjects: | Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software | ||||||
Divisions: | Faculty of Science, Engineering and Medicine > Science > Computer Science | ||||||
Publisher: | IEEE | ||||||
ISBN: | 9781728106229 | ||||||
Official Date: | 2018 | ||||||
Dates: |
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DOI: | 10.1109/IWBF.2019.8739218 | ||||||
Status: | Peer Reviewed | ||||||
Publication Status: | Published | ||||||
Access rights to Published version: | Restricted or Subscription Access | ||||||
Date of first compliant deposit: | 15 May 2020 | ||||||
Funder: | Mexico. Secretaría de Educación Pública, Consejo Nacional de Ciencia y Tecnología, H2020 European Research Council | ||||||
Grant number: | 690907 | ||||||
Conference Paper Type: | Paper | ||||||
Title of Event: | 2019 7th International Workshop on Biometrics and Forensics (IWBF) | ||||||
Type of Event: | Workshop | ||||||
Location of Event: | Cancun, Mexico, Mexico | ||||||
Date(s) of Event: | 2-3 May 2019 |
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