Abstract: A system uses range and Doppler velocity measurements from a lidar subsystem and images from a video subsystem to estimate a six degree-of-freedom trajectory of a target. The video subsystem and the lidar subsystem may be aligned with one another, and hence calibrated, by determining, for example, a centroid of an iris determined from the lidar subsystem and a centroid of the iris determined from the video subsystem and determining a calibration offset between the two centroids.

Abstract: Systems and methods for controlling camera settings of a camera to improve detection of faces in an uncontrolled environment are described. A first image is received from the camera, where the first image is captured by the camera at a first set of camera settings. A face is detected in the first image. The camera is adjusted to a second set of camera settings based on the detected face, where the second set of camera settings different from the first set of camera settings. A second image is received from the camera, where the second image is captured by the camera at the second set of camera settings. The face is detected in the second image. A quality metric of the face in the second image is determined where the quality metric is indicative of an image quality of the face in the second image.

Abstract: Detecting position information related to a face, and more particularly to an eyeball in a face, using a detection and ranging system, such as a Radio Detection And Ranging (“RADAR”) system, or a Light Detection And Ranging (“LIDAR”) system. The position information may include a location of the eyeball, translational motion information related to the eyeball (e.g., displacement, velocity, acceleration, jerk, etc.), rotational motion information related to the eyeball (e.g., rotational displacement, rotational velocity, rotational acceleration, etc.) as the eyeball rotates within its socket.

Abstract: A system and method for improving a video characteristic of a video stream is described. According to various implementations of the invention, a changed region between a later-in-time image frame and an earlier-in-time image frame and an unchanged region between such two image frames are determined. A new improvement to the video characteristic is determined and applied to the changed region of the later-in-time image frame. A prior improvement to the video characteristic that was determined for the earlier-in-time image frame is applied to the unchanged region of the later-in-time image frame.

Abstract: Systems and methods for determining ranges to a target disposed behind a transparent surface are described. A target acquisition system receives a plurality of lidar returns, at least some of which are from a target and at least some of which are from a transparent surface. The lidar returns correspond to a portion of a lidar signal generated by a lidar, directed toward the target, and reflected back to the lidar from either the target or the transparent surface. A range measurement for each of the plurality of lidar returns is determined. The target acquisition system generates a histogram of the range measurements. The histogram includes an array including a plurality of range bins. Each range bin defines a unique portion of a predetermined distance out from the lidar. The histogram further includes a count associated with each respective range bin.

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 and generate a three-dimensional image of the target. The system may refine the three-dimensional image by reducing the stochastic components in the transformation parameters between video frame times.

Abstract: A system and method for detecting a potential match between a candidate facial image and a dataset of facial images is described. Some implementations of the invention determine whether a candidate facial image (or multiple facial images) of a person taken, for example, at point of entry corresponds to one or more facial images stored in a dataset of persons of interest (e.g., suspects, criminals, terrorists, employees, VIPs, “whales,” etc.). Some implementations of the invention detect potential fraud in a dataset of facial images. In a first form of potential fraud, a same facial image is associated with multiple identities. In a second form of potential fraud, different facial images are associated with a single identity, as in the case, for example, of identity theft. According to various implementations of the invention, spectral clustering techniques are used to determine a likelihood that pairs of facial images (or pairs of facial image sets) correspond to the person or different persons.

Abstract: Systems and methods for controlling camera settings of a camera to improve detection of faces in an uncontrolled environment are described. A first image is received from the camera, where the first image is captured by the camera at a first set of camera settings. A face is detected in the first image. The camera is adjusted to a second set of camera settings based on the detected face, where the second set of camera settings different from the first set of camera settings. A second image is received from the camera, where the second image is captured by the camera at the second set of camera settings. The face is detected in the second image. A quality metric of the face in the second image is determined where the quality metric is indicative of an image quality of the face in the second image.

Abstract: Detecting position information related to a face, and more particularly to an eyeball in a face, using a detection and ranging system, such as a Radio Detection And Ranging (“RADAR”) system, or a Light Detection And Ranging (“LIDAR”) system. The position information may include a location of the eyeball, translational motion information related to the eyeball (e.g., displacement, velocity, acceleration, jerk, etc.), rotational motion information related to the eyeball (e.g., rotational displacement, rotational velocity, rotational acceleration, etc.) as the eyeball rotates within its socket.

Abstract: A system and method for improving a video characteristic of a video stream is described. According to various implementations of the invention, a changed region between a later-in-time image frame and an earlier-in-time image frame and an unchanged region between such two image frames are determined. A new improvement to the video characteristic is determined and applied to the changed region of the later-in-time image frame. A prior improvement to the video characteristic that was determined for the earlier-in-time image frame is applied to the unchanged region of the later-in-time image frame.

Abstract: Systems and methods for determining ranges to a target disposed behind a transparent surface are described. A target acquisition system receives a plurality of lidar returns, at least some of which are from a target and at least some of which are from a transparent surface. The lidar returns correspond to a portion of a lidar signal generated by a lidar, directed toward the target, and reflected back to the lidar from either the target or the transparent surface. A range measurement for each of the plurality of lidar returns is determined. The target acquisition system generates a histogram of the range measurements. The histogram includes an array including a plurality of range bins. Each range bin defines a unique portion of a predetermined distance out from the lidar. The histogram further includes a count associated with each respective range bin.

Abstract: A laser radar system using collocated laser beams to unambiguously detects a range of a target and a range rate at which the target is moving relative to the laser radar system. Another aspect of various embodiments of the invention may relate to a laser radar system that uses multiple laser radar sections to obtain multiple simultaneous measurements (or substantially so), whereby both range and range rate can be determined without various temporal effects introduced by systems employing single laser sections taking sequential measurements. In addition, other aspects of various embodiments of the invention may enable faster determination of the range and rate of the target, a more accurate determination of the range and rate of the target, and/or may provide other advantages.

Abstract: A system and method for detecting a potential match between a candidate facial image and a dataset of facial images is described. Some implementations of the invention determine whether a candidate facial image (or multiple facial images) of a person taken, for example, at point of entry corresponds to one or more facial images stored in a dataset of persons of interest (e.g., suspects, criminals, terrorists, employees, VIPs, “whales,” etc.). Some implementations of the invention detect potential fraud in a dataset of facial images. In a first form of potential fraud, a same facial image is associated with multiple identities. In a second form of potential fraud, different facial images are associated with a single identity, as in the case, for example, of identity theft. According to various implementations of the invention, spectral clustering techniques are used to determine a likelihood that pairs of facial images (or pairs of facial image sets) correspond to the person or different persons.

Abstract: Systems and methods for controlling camera settings of a camera to improve detection of faces in an uncontrolled environment are described. A first image is received from the camera, where the first image is captured by the camera at a first set of camera settings. A face is detected in the first image. The camera is adjusted to a second set of camera settings based on the detected face, where the second set of camera settings different from the first set of camera settings. A second image is received from the camera, where the second image is captured by the camera at the second set of camera settings. The face is detected in the second image. A quality metric of the face in the second image is determined where the quality metric is indicative of an image quality of the face in the second image.

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 estimates this trajectory in two stages: a first stage in which the range and Doppler measurements from the lidar system along with various feature measurements obtained from the images from the video system are used to estimate first stage motion aspects of the target (i.e., the trajectory of the target); and a second stage in which the images from the video system and the first stage motion aspects of the target are used to estimate second stage motion aspects of the target. Once the second stage motion aspects of the target are estimated, a three-dimensional image of the target may be generated.

Abstract: A system uses range and Doppler velocity measurements from a lidar subsystem and images from a video subsystem to estimate a six degree-of-freedom trajectory of a target. The video subsystem and the lidar subsystem may be aligned with one another, and hence calibrated, by determining, for example, a centroid of an iris determined from the lidar subsystem and a centroid of the iris determined from the video subsystem and determining a calibration offset between the two centroids.

Abstract: Systems and methods for controlling camera settings of a camera to improve detection of faces in an uncontrolled environment are described. A first image is received from the camera, where the first image is captured by the camera at a first set of camera settings. A face is detected in the first image. The camera is adjusted to a second set of camera settings based on the detected face, where the second set of camera settings different from the first set of camera settings. A second image is received from the camera, where the second image is captured by the camera at the second set of camera settings. The face is detected in the second image. A quality metric of the face in the second image is determined where the quality metric is indicative of an image quality of the face in the second image.

Abstract: A method for terminating a plurality of optical fibers arranged in a two-dimensional arrangement comprises inserting the plurality of optical fibers into and through a fiber ferrule, where the fiber ferrule has a plurality of parallel channels extending from an entry surface through to a polish surface; polishing the polish surface including an end of each of the plurality of optical fibers to form a coplanar surface at a polish angle relative to a reference plane perpendicular to the parallel channels; and affixing a glass plate to the polish surface.