Title:
METHODS AND SYSTEMS FOR MULTIMODAL HAND STATE PREDICTION
Document Type and Number:
WIPO Patent Application WO/2023/178984
Kind Code:
A1
Abstract:
Methods and systems are described for generating hand state predictions. A hand state prediction system (200) includes a machine learning-based model, such as a neural network model, that is trained to convert inertial motion measurements and surface contact data into predictions of a corresponding hand gesture or gripping posture. For each window of data sampled, motion data (230) and contact data (250) are obtained, processed and fused to generate a fused prediction. The hand state prediction system (200) can operate in continuous mode to automatically detect a start and an end of a hand action, or a user can designate a start and an end of a hand action. The hand state predictions are generated by a multimodal classifier (360) by processing the fused prediction. Instructions represented by a hand action can be acted upon through a command action performed by a computing device or a computer application.
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Inventors:
CODY ROYA (CA)
HUANG DA-YUAN (CA)
CAO XIANG (CA)
LI WEI (CA)
HUANG DA-YUAN (CA)
CAO XIANG (CA)
LI WEI (CA)
Application Number:
PCT/CN2022/123548
Publication Date:
September 28, 2023
Filing Date:
September 30, 2022
Export Citation:
Assignee:
HUAWEI TECH CO LTD (CN)
International Classes:
G06F3/01
Foreign References:
| US20220043517A1 | 2022-02-10 | |||
| CN113849068A | 2021-12-28 | |||
| CN106598243A | 2017-04-26 | |||
| CN106575200A | 2017-04-19 | |||
| CN112114665A | 2020-12-22 | |||
| CN112492090A | 2021-03-12 | |||
| CN113205074A | 2021-08-03 | |||
| US20080211766A1 | 2008-09-04 | |||
| KR20200005243A | 2020-01-15 |
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