3D convolutional neural networks for automatic human action recognition
US8345984B2 · kind B2 · utility
82Cited by
1References
18Claims
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Key dates
| Filing date | Jun 11, 2010 |
| Grant date | Jan 1, 2013 |
| Priority date | — |
| Expiry date | Jul 1, 2031 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/084
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Systems and methods are disclosed to recognize human action from one or more video frames by performing 3D convolutions to capture motion information encoded in multiple adjacent frames and extracting features from spatial and temporal dimensions therefrom; generating multiple channels of information from the video frames, combining information from all channels to obtain a feature representation for a 3D CNN model; and applying the 3D CNN model to recognize human actions.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.