Title:
METHOD AND KIT FOR RECOGNISING A USER OF A FOOTWEAR ARTICLE OR AN ACTIVITY PERFORMED BY A USER OF A FOOTWEAR ARTICLE
Document Type and Number:
WIPO Patent Application WO/2022/214523
Kind Code:
A1
Abstract:
The invention relates to the field involving the performance of activities. In particular, the invention relates to a method and kit for recognising a user of a footwear article or an activity performed by a user of a footwear article. One of the objectives of the invention is to facilitate the detection of a user of a footwear article or of an activity performed by a user of a footwear article. For this purpose, the inventors propose the use of raw sensor data from the footwear article, which data is supplied to a machine-learning-trained classifier. The inventors have discovered that the use of raw sensor data, without fusion, by a classifier allows surprisingly good results to be obtained in the recognition of a subject or of different activities performed by a subject. In particular, the invention uses the embedding technique to project the raw data in a data representation space that is suitable for the desired classification.
Inventors:
OUMNIA KARIM (FR)
OUDRHIRI RADOUANE (FR)
OUDRHIRI RADOUANE (FR)
Application Number:
PCT/EP2022/059073
Publication Date:
October 13, 2022
Filing Date:
April 06, 2022
Export Citation:
Assignee:
ZHOR TECH (FR)
International Classes:
G06K9/00; G06K9/62
Foreign References:
| US20190365287A1 | 2019-12-05 |
Other References:
QIN ZOU ET AL: "Deep Learning Based Gait Recognition Using Smartphones in the Wild", ARXIV.ORG, CORNELL UNIVERSITY LIBRARY, 201 OLIN LIBRARY CORNELL UNIVERSITY ITHACA, NY 14853, 1 November 2018 (2018-11-01), XP081454777
Attorney, Agent or Firm:
A.P.I. CONSEIL (FR)
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