Systems and methods for 3D facial modeling
AssigneeAdeia Imaging LLC
InventorKartik Venkataraman
Life of this patent
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Abstract
In an embodiment, a 3D facial modeling system includes a plurality of cameras configured to capture images from different viewpoints, a processor, and a memory containing a 3D facial modeling application and parameters defining a face detector, wherein the 3D facial modeling application directs the processor to obtain a plurality of images of a face captured from different viewpoints using the plurality of cameras, locate a face within each of the plurality of images using the face detector, wherein the face detector labels key feature points on the located face within each of the plurality of images, determine disparity between corresponding key feature points of located faces within the plurality of images, and generate a 3D model of the face using the depth of the key feature points.
Claims20
A method for animating a three-dimensional (3D) model of a face based on frames of video containing the face, comprising:
- obtaining a first image and a second image containing a human face;
- locating the human face within the first image using a face detector, where the face detector is configured to label key feature points of the human face, where the key feature points comprise at least one eye;
- determining a depth value for each key feature point;
- providing the determined depth value for each key feature point to a neural network to produce a 3D model of the human face;
- tracking a difference in pose of the human face between the first image and the second image;
- and
- animating the 3D model based on the tracked difference.
A method for three-dimensional (3D) face modeling, comprising:
- obtaining an image containing a human face;
- locating the human face within the image using a face detector, where the face detector is configured to label key feature points of the human face, wherein the key feature points comprise at least one eye;
- determining a depth value for each key feature point;
- and
- providing the determined depth value for each key feature point to a neural network.
Dependencies are inferred from the claim text.