Method of training neural networks for hand pose detection
US10503270B2 · kind B2 · utility
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Key dates
| Filing date | Jun 10, 2019 |
| Grant date | Dec 10, 2019 |
| Priority date | — |
| Expiry date | Jun 10, 2039 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH04N13/271
- WIPO fieldAudio-visual technology
- WIPO sectorElectrical engineering
Abstract
A method for training a hierarchy of trained neural networks for hand pose detection includes training a first neural network to generate a first plurality of activation features that classify an input depth map data corresponding to a hand based on a wrist angle of the hand, the training using a plurality of depth maps of a hand with predetermined wrist angles as inputs to the first neural network during the training, and storing the first neural network in a memory after the training for use in classifying an additional depth map corresponding to a hand based on an angle of a wrist of the hand in the additional depth map.
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