Owl Autonomous Imaging, Inc.

Francis J Cusack, Jr

Eugene Michael Petilli

Charles F Gershman

Srinath Obla

Akash Chintha

Christopher S Urban

A first light beam transmits from a first location to a region of interest at a time tand reflects off at least one object disposed in the region of interest, producing a first reflected light beam. A time of flight (ToF) counter is incremented until the reflected first light beam is received back at the first location, whereupon ToF counter stops at time t. A second light beam transmits from the first location to the region of interest at time tsubsequent to time tand reflects off the least one object to produce a second reflected light beam. ToF counter is decremented, starting from first count value, until the reflected second light beam is received back at the first location, whereupon ToF counter stops at time t. A real-time velocity of the object is computed based at least in part on t, t, t, and t.

System, method, and apparatus for object velocity and acceleration measurement in imaging system

Embodiments of systems and methods for multi-aperture ranging are disclosed. An embodiment of an image processing system includes at least one processor and memory configured to receive a multi-aperture image set that includes a high-resolution subaperture image and a low-resolution subaperture image, wherein the high-resolution subaperture image and the low-resolution subaperture image were captured simultaneously from a camera using dissimilar focal lengths, predict a high-resolution predicted disparity map from the high-resolution subaperture image using a neural network, predict a low-resolution predicted disparity map from the low-resolution subaperture image using the neural network, and generate an integrated range map from the high-resolution and low-resolution predicted disparity maps, wherein the integrated range map includes an array of range information that corresponds to the multi-aperture image set and that is generated by overlaying common points in both the high-resolution predicted disparity map and the low-resolution predicted disparity map.

Multi-aperture ranging devices and methods

A method for image acquisition includes receiving, by an image acquisition computing device, a digitized LiDAR image frame and a thermal image frame of a region of interest from a read out integrated circuit of an image acquisition device coupled to the image acquisition computing device. The LiDAR image frame and the thermal image frame are processed to detect one or more objects of interest located in the region of interest. The detected one or more objects of interest are correlated between the LiDAR image frame and the thermal image frame. The detected one or more objects of interest are identified based on the correlation between the LiDAR image frame and the thermal image frame. An integrated LiDAR and thermal image acquisition device is also disclosed.

Two-waveband image acquisition devices and methods of use

Embodiments of systems and methods for multi-aperture ranging are disclosed. An embodiment of a device includes a main lens, configured to receive an image from the field of view of the main lens, a multi-aperture optical component having optical elements optically coupled to the main lens and configured to create a multi-aperture image set that includes a plurality of subaperture images, wherein at least one point in the field of view is captured by at least two of the subaperture images, an array of sensing elements, a ROIC configured to receive the signals, to convert the signals to digital data, and to output the digital data, and an image processing system, responsive to the digital data that is output from the ROIC, which is configured to generate disparity values that correspond to at least one point in common between the at least two subaperture images.

Growing community of inventors

Wilmington, NC, United States of America

Francis J Cusack, Jr