Shen et al., 2024 - Google Patents
Towards Open-World Gesture RecognitionShen et al., 2024
View PDF- 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 …
- 238000000034 method 0 abstract description 92
Classifications
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- G06F3/01—Input arrangements or combined input and output arrangements for interaction between user and computer
- G06F3/011—Arrangements for interaction with the human body, e.g. for user immersion in virtual reality
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- G06F3/01—Input arrangements or combined input and output arrangements for interaction between user and computer
- G06F3/017—Gesture based interaction, e.g. based on a set of recognized hand gestures
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- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/6267—Classification techniques
- G06K9/6268—Classification techniques relating to the classification paradigm, e.g. parametric or non-parametric approaches
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- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
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- G06—COMPUTING; CALCULATING; COUNTING
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