Aeva, Inc.

Stereovision Imaging, Inc.

Digital Signal Corporation

Chris Roller

Péter L Venetianer

Randall J St Romain, Ii

Miraj Shah

Richard Lee Sebastian

Anatoley T Zheleznyak

Gavin Rosenbush

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.

System and method for intelligent camera control

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.

System and method for field calibrating video and lidar subsystems using facial features

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Fairfax Station, VA, United States of America

Chris Roller