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Shen et al., 2024 - Google Patents

Towards Open-World Gesture Recognition

Shen et al., 2024

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Document ID
11646268598397807491
Author
Shen J
De Lange M
Xu X
Zhou E
Tan R
Suda N
Lazarewicz M
Kristensson P
Karlson A
Strasnick E
et al.
Publication year
Publication venue
arXiv preprint arXiv:2401.11144

External Links

Snippet

Static machine learning methods in gesture recognition assume that training and test data come from the same underlying distribution. However, in real-world applications involving gesture recognition on wrist-worn devices, data distribution may change over time. We …
Continue reading at arxiv.org (PDF) (other versions)

Classifications

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    • G06F3/011Arrangements for interaction with the human body, e.g. for user immersion in virtual reality
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
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    • G06F3/01Input arrangements or combined input and output arrangements for interaction between user and computer
    • G06F3/017Gesture based interaction, e.g. based on a set of recognized hand gestures
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    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F3/00Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
    • G06F3/01Input arrangements or combined input and output arrangements for interaction between user and computer
    • G06F3/03Arrangements for converting the position or the displacement of a member into a coded form
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    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62Methods or arrangements for recognition using electronic means
    • G06K9/6217Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
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    • G06N99/00Subject matter not provided for in other groups of this subclass
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