Bae Systems, Inc.

James Duncan Revell

Roderick Buchanan

Mark Robert Goodall

Gary Martin Cross

An optical inertial measurement method for determining a 6DOF pose in respect of a moving platform, the method comprising providing, in respect of said moving platform, a camera unit () comprised of at least three monocular cameras () connected rigidly together and configured such that their fields of view do not overlap and cover motion of said platform in each of three principal, substantially orthogonal axes; receiving video outputs from each of said cameras; determining individual point correspondences from said video outputs, and estimating therefrom, for each camera, a transform that includes translation values representative of direction of translation in the x and y axes, rotation about the optical axis and a scale factor, each transform being expressed with respect to a local 3D coordinate system associated with a respective camera; and mapping said translation values in the x and y axes to a global 3D coordinate system, having its origin defined by a point between said cameras, and multiplying said translation values by a respective scale factor so as to determine a 6DOF pose in respect of said camera unit. An optical inertial measurement system is also disclosed.

Optical inertial measurement apparatus and method

Disclosed is a method and apparatus for detecting cloud features. The method comprises: obtaining image data (e.g. using a camera), the image data defining a plurality of pixels and, for each pixel, a respective luminance value; defining one or more intervals for the luminance values of the pixels; partitioning the image data into one or more image segments (-), each respective image segment (-) containing pixels having a luminance value in a respective interval; and classifying, as a cloud feature, each image segment (-) containing pixels having luminance value greater than or equal to a threshold luminance value (L).

Cloud feature detection

Disclosed is a method and apparatus for detecting and ranging cloud features. The method comprises: obtaining image data (e.g. using a camera (); classifying, as a cloud feature, an image segment (-) of the image data; determining a plurality of moments of the image segment (-); using the determined plurality of moments, determining a geometric representation of that image segment (-); and, using the geometric representation, determining a distance between the cloud feature represented by that image segment (-) and an entity that obtained the image data.

Detecting and ranging cloud features

Disclosed are apparatus and a method for detecting cloud features. The method comprises: obtaining () image data (); identifying () regions of the image data corresponding to a below-horizon region and an above-horizon region; classifying () one or more parts of the above-horizon region as a cloud feature; determining () an identification model specifying a visual appearance of some or all of the parts of the above-horizon region that have been classified as a cloud feature; and using the determined identification model, classifying (), as cloud features, those regions of the of the below-horizon region whose visual appearance is as specified by the identification model.

A method and apparatus for identifying and analyzing an aircraft landing site during flight is provided. The method includes the steps of using image capture means such as an infrared camera to capture in-flight images of the ground in the region of a possible landing site, using a database of computer modelled images of possible aircraft landing sites mapped to a global co-ordinate reference frame to compare the in-flight images with a modelled image of the possible landing site and optimizing correspondence between the two images to obtain an in-flight image optimally mapped to the global co-ordinate reference frame. Thereafter, the landing site which corresponds to the optimally mapped in-flight image is analyzed to ascertain the presence of any obstructions such as life forms, vehicles or newly erected buildings thereon.

Identification and analysis of aircraft landing sites

A method of detecting at least one moving vehicle includes receiving () image data representing a sequence of image frames over time. The method further includes analyzing (-) the image data to identify potential moving vehicles, and comparing (-) at least one said potential moving vehicle with a vehicle movement model that defines a trajectory of a potential moving vehicle to determine whether the at least one potential moving vehicle conforms with the model.

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Bristol, United Kingdom

James Duncan Revell