System and Method for Off Angle Three-Dimensional Face Standardization for Robust Performance
First Claim
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1. A system for obtaining 3D standardized face representations from non-frontal face views, the system comprising:
- a lidar subsystem configured to direct at least two beams toward the target and generate a plurality of three-dimensional (3D) measurements for a plurality of points on the target for each of the at least two beams;
a video subsystem configured to provide a plurality of two-dimensional images of the target; and
a processor configured to;
receive, from the lidar subsystem, the plurality of 3D measurements for the plurality of points on the target,receive, from the video subsystem, the plurality of 2D images of the target,generate at least one 3D image of the target based on the 3D measurements for the plurality of points on the target and the 2D images of the target,determine a non-frontal 3D face representation based on the at least one 3D image,transform the non-frontal 3D face representation to a frontal 3D face representation,generate a mirror face representation of the frontal 3D face representation, andgenerate a 3D standardized face representation by filling one or more missing regions in the frontal 3D face representation based on data from the mirror face representation.
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Abstract
A system uses range and Doppler velocity measurements from a lidar system and images from a video system to estimate a six degree-of-freedom trajectory of a target. The system utilizes a two-stage solution to obtain 3D standardized face representations from non-frontal face views for a statistical learning algorithm. The first stage standardizes the pose (non-frontal 3D face representation) to a frontal view and the second stage uses facial symmetry to fill in missing facial regions due to yaw face pose variations (i.e. rotation about the y-axis).
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4 Claims
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1. A system for obtaining 3D standardized face representations from non-frontal face views, the system comprising:
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a lidar subsystem configured to direct at least two beams toward the target and generate a plurality of three-dimensional (3D) measurements for a plurality of points on the target for each of the at least two beams; a video subsystem configured to provide a plurality of two-dimensional images of the target; and a processor configured to; receive, from the lidar subsystem, the plurality of 3D measurements for the plurality of points on the target, receive, from the video subsystem, the plurality of 2D images of the target, generate at least one 3D image of the target based on the 3D measurements for the plurality of points on the target and the 2D images of the target, determine a non-frontal 3D face representation based on the at least one 3D image, transform the non-frontal 3D face representation to a frontal 3D face representation, generate a mirror face representation of the frontal 3D face representation, and generate a 3D standardized face representation by filling one or more missing regions in the frontal 3D face representation based on data from the mirror face representation. - View Dependent Claims (2, 3, 4)
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Specification