Embodiments of the invention provide a camera array imaging architecture that computes depth maps for objects within a scene captured by the cameras, and use a near-field sub-array of cameras to compute depth to near-field objects and a far-field sub-array of cameras to compute depth to far-field objects. In particular, a baseline distance between cameras in the near-field subarray is less than a baseline distance between cameras in the far-field sub-array in order to increase the accuracy of the depth map. Some embodiments provide an illumination near-IR light source for use in computing depth maps.

A method for surveying an environment by a movable surveying instrument configured to be carried by a human with a progressional capturing of 2D-images by at least one camera and applying a visual simultaneous location and mapping algorithm (VSLAM) or a visual inertial simultaneous location and mapping algorithm (VISLAM) with a progressional deriving of a sparse evolving point cloud of at least part of the environment, and a progressional deriving of a trajectory of movement. The method comprises a progressional matching of the sparse evolving point cloud with a known CAD-geometry, with a minimizing of a function configured to model a distance between the sparse point cloud and the known CAD-geometry and deriving a spatial localization and orientation of the surveying instrument. At least one surveying measurement value of the environment by a spatial measurement unit is combined with the sparse point cloud or the plan information.

A method of targeting, which involves capturing a first video of a scene about a potential targeting coordinate by a first video sensor on a first aircraft; transmitting the first video and associated potential targeting coordinate by the first aircraft; receiving the first video on a first display in communication with a processor, the processor also receiving the potential targeting coordinate; selecting the potential targeting coordinate to be an actual targeting coordinate for a second aircraft in response to viewing the first video on the first display; and guiding a second aircraft toward the actual targeting coordinate; where positive identification of a target corresponding to the actual targeting coordinate is maintained from selection of the actual targeting coordinate.

A method of targeting, which involves capturing a first video of a scene about a potential targeting coordinate by a first video sensor on a first aircraft; transmitting the first video and associated potential targeting coordinate by the first aircraft; receiving the first video on a first display in communication with a processor, the processor also receiving the potential targeting coordinate; selecting the potential targeting coordinate to be an actual targeting coordinate for a second aircraft in response to viewing the first video on the first display; and guiding a second aircraft toward the actual targeting coordinate; where positive identification of a target corresponding to the actual targeting coordinate is maintained from selection of the actual targeting coordinate.

Systems and methods for structure footprint detection from oblique imagery are disclosed, including a computer system configured to receive geo-referenced oblique images; analyze pixels of the images to: identify pixels representing a structure with walls; determine ground locations for the walls, geographic locations and orientations of pixels representing vertical edges of the walls, and relative lengths of the walls to produce horizontal line segments representing the base of the walls and having a relative length and an orientation, the horizontal line segment(s) determined from horizontal edge(s) extending a length between vertical edges above the bottoms of the vertical edges such that the horizontal edge is above the base of the structure; and assemble the horizontal line segments based on their relative lengths and orientations to form a footprint of the structure.

Systems and methods for structure footprint detection from oblique imagery are disclosed, including a computer system configured to receive geo-referenced oblique images; analyze pixels of the images to: identify pixels representing a structure with walls; determine ground locations for the walls, geographic locations and orientations of pixels representing vertical edges of the walls, and relative lengths of the walls to produce horizontal line segments representing the base of the walls and having a relative length and an orientation, the horizontal line segment(s) determined from horizontal edge(s) extending a length between vertical edges above the bottoms of the vertical edges such that the horizontal edge is above the base of the structure; and assemble the horizontal line segments based on their relative lengths and orientations to form a footprint of the structure.

According to an aspect, there is provided a method comprising controlling a structural light source of a modelling arrangement to produce a diffraction pattern of a known geometry on a surface to be modeled, the diffraction pattern accurately complying with a mathematical-physical model and wherein beam output angles of the diffraction pattern are accurately known based on the mathematical-physical model; recording a first image of the surface comprising the diffraction pattern with a first camera and a second image of the surface comprising the diffraction pattern with a second camera substantially simultaneously; determining a point cloud comprising primary points from the diffraction pattern visible in the first image; identifying the corresponding primary points from the second image; and using each primary point of the point cloud in the first and second images as an initial point for search spaces for secondary points in the first and second images.

In variants, the method can include: detecting a property within a set of measurements; determining a set of property parameters based on the detection; determining a set of higher-resolution measurements based on the set of property parameters; and determining a set of property attributes based on the set of higher-resolution measurements.

In variants, the method can include: detecting a property within a set of measurements; determining a set of property parameters based on the detection; determining a set of higher-resolution measurements based on the set of property parameters; and determining a set of property attributes based on the set of higher-resolution measurements.

The present invention relates to the efficient use of both local and remote computational resources and communication bandwidth to provide distributed environment mapping using a plurality of mobile sensor-equipped devices. According to a first aspect, there is provided a method of determining a global position of one or more landmarks on a global map, the method comprising the steps of determining one or more differences between sequential sensor data captured by one or more moving devices; determining one or more relative localisation landmark positions with respect to the one or more moving devices; determining relative device poses based one or more differences between sequential sensor data relative to the one or more relative localisation landmark positions; and determining a correlation between each device pose and the one or more relative localisation landmarks positions.