Predicting depth from image data using a statistical model
US11100401B2 · kind B2 · utility
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Key dates
| Filing date | Sep 12, 2017 |
| Grant date | Aug 24, 2021 |
| Priority date | — |
| Expiry date | May 2, 2038 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/20084
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Systems and methods are described for predicting depth from colour image data using a statistical model such as a convolutional neural network (CNN), The model is trained on binocular stereo pairs of images, enabling depth data to be predicted from a single source colour image. The model is trained to predict, for each image of an input binocular stereo pair, corresponding disparity values that enable reconstruction of another image when applied, to the image. The model is updated based on a cost function that enforces consistency between the predicted disparity values for each image in the stereo pair.
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