Alexandria, VA, United States
Alexandria, VA, United States

Time filter

Source Type

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.


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).


Patent
Digital Signal | Date: 2016-07-12

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.


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 by mapping the measurements of various facial features obtained by each of the subsystems to one another.


Patent
Digital Signal | Date: 2016-01-01

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.


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.


Various implementations of the invention perform facial recognition on a target image compared against a color image from an image gallery, where the target image was acquired by an infrared-sensitive camera of a target that was illuminated with infrared light. According to various implementations of the invention, a blue component and a green component of the pixels in the color image are suppressed or eliminated, and facial recognition is performed between the target image and the color-suppressed image.


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. The count corresponds to a number of range measurements falling within the unique portion of the predetermined distance corresponding to that respective range bin. In some implementations of the invention, the target acquisition system determines which of the range measurements correspond to the target based on the histogram. In some implementations of the invention, the target acquisition system determines which of the range measurements correspond to the transparent surface based on the histogram.


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.


Patent
Digital Signal | Date: 2015-06-05

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. The camera is adjusted to a new set of camera settings to increase the quality metric of the face in subsequent images, the new set of camera settings different from both the first set of camera settings and the second set of camera settings. Once a sufficient quality metric of the face is achieved, the face is acquired, or otherwise captured, by the camera or other sensors.

Loading Digital Signal collaborators
Loading Digital Signal collaborators