System and method for pose-invariant face alignment
AssigneeRobert Bosch GmbH
InventorsMao Ye, Liu Ren, Amin Jourabloo
Life of this patent
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Abstract
A computing system includes a processing system with at least one processing unit. The processing system is configured to execute a face alignment method upon receiving image data with a facial image. The processing system is configured to apply a neural network to the facial image. The neural network is configured to provide a final estimate of parameter data for the facial image based on the image data and an initial estimate of the parameter data. The neural network includes at least one visualization layer, which is configured to generate a feature map based on a current estimate of the parameter data. The parameter data includes head pose data and face shape data.
Claims17
A computing system comprising a processing system with at least one processing unit, the processing system being configured to execute a face alignment method that includes:
- receiving image data associated with a facial image;
- and
- implementing a neural network to provide a final estimate of parameter data for the facial image based on the image data and an initial estimate of the parameter data, the neural network being configured to generate a feature map based on a current estimate of the parameter data,
- wherein:
- the neural network is a single convolutional neural network with a plurality of visualization blocks that are connected;
- each visualization block includes at least a visualization layer, convolutional layers, and fully connected layers;
- and
- the parameter data includes head pose data and face shape data.
A computer-implemented method for face alignment comprising:
- receiving image data associated with a facial image;
- and
- implementing a neural network to provide a final estimate of parameter data for the facial image based on the image data and an initial estimate of the parameter data, the neural network including at least one visualization layer that is configured to generate a feature map based on a current estimate of the parameter data,
- wherein:
- each visualization layer utilizes a mask to differentiate between pixels in different parts of the facial image and make pixel values of visualized images similar across different head poses;
- and
- the parameter data includes head pose data and face shape data.
Non-transitory computer-readable media comprising at least computer-readable data that, when executed by a processing system with at least one processing unit, performs a face alignment method that includes:
- receiving image data associated with a facial image;
- and
- implementing a neural network to provide a final estimate of parameter data for the facial image based on the image data and an initial estimate of the parameter data, the neural network being configured to generate a feature map based on a current estimate of the parameter data,
- wherein:
- the neural network is a single convolutional neural network with a plurality of visualization blocks that are connected;
- each visualization block includes at least one visualization layer, convolutional layers, and fully connected layers;
- and
- the parameter data includes head pose data and face shape data.
Dependencies are inferred from the claim text.