Deep learning for three dimensional (3D) gaze prediction
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United States of America
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Feb 11, 2020
Grant Date -
Oct 3, 2019
app pub date -
Mar 30, 2018
filing date -
Mar 30, 2018
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Abstract
Techniques for generating 3D gaze predictions based on a deep learning system are described. In an example, the deep learning system includes a neural network. A scaled image is generated from 2D image showing a user face based on a rough distance between the user eyes and a camera that generated the 2D image. Image crops at different resolutions are generated from the scaled image and include a crop around each of the user eyes and a crop around the user face. These crops are input to the neural network. In response, the neural network outputs a distance correction and a 2D gaze vector per user eye. A corrected eye-to-camera distance is generated by correcting the rough distance based on the distance correction. A 3D gaze vector for each of the user eyes is generated based on the corresponding 2D gaze vector and the corrected distance.
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