Abstract: A system and method for performing facial recognition is described. In some implementations, the system and method identify points of a three-dimensional scan that are associated with occlusions, such as eyeglasses, to a face of a target subject and remove the identified points from the three-dimensional scan.

Abstract: A system and method for performing facial recognition is described. In some implementations, the system and method identify points of a three-dimensional scan that are associated with occlusions, such as eyeglasses, to a face of a target subject and remove the identified points from the three-dimensional scan.

Abstract: A system and method for performing facial recognition is described. In some implementations, the system and method identify points of a three-dimensional scan that are associated with occlusions, such as eyeglasses, to a face of a target subject and remove the identified points from the three-dimensional scan.

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).

Abstract: A system and method for performing facial recognition is described. In some implementations, the system and method identify points of a three-dimensional scan that are associated with occlusions, such as eyeglasses, to a face of a target subject and remove the identified points from the three-dimensional scan.

Abstract: A system and method for performing facial recognition is described. In some implementations, the system and method identify points of a three-dimensional scan that are associated with occlusions, such as eyeglasses, to a face of a target subject and remove the identified points from the three-dimensional scan.

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).

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).