Described herein are passive systems and methods for ranging objects. The systems and methods are passive in that they do not rely on transmission of radiation (whether radiofrequency, visible, infrared, ultraviolet, acoustic, etc.) to determine range. The systems and methods described herein may be used both in civilian and military applications. The present techniques allow users to determine range to moving targets, which is notoriously difficult to estimate using the human eye. The present techniques perform ranging to a target using artificial intelligence models, including object segmentation and pose estimation. Object segmentation may involve determining a dimension (e.g., height) of a specified target in an image, in terms of pixels. If there are multiple objects in the scene, range estimates may be calculated using object segmentation for each object. Pose estimation involves a machine learning technique that identifies sets of coordinates corresponding to joint keypoints.

A firearm system includes a firearm and a computer. Electronics in the firearm determine data that includes a pathway between different points of aim of the firearm as the firearm moves. The computer receives this data and builds an image of the pathway between the different points of aim of the firearm.

Search points in a search space may be projected onto images from cameras imaging different parts of the search space. Subimages, corresponding to the projected search points, may be selected and processed to determine if a target object has been detected. Based on subimages in which target objects are detected, as well as orientation data from cameras capturing images from which the subimages were selected, positions of the target objects in the search space may be determined.

A remote weapon control device for controlling a weapon having a photographing device is provided. The remote weapon control device includes: a communication interface configured to receive an image captured by the photographing device; an object extractor configured to extract objects from the image; a target extractor configured to extract targets from the objects; a shooting order determinator configured to determine an order of the targets for shooting; and a control signal generator configured to generate a shooting control signal for controlling the weapon to shoot the targets in the determined order.

A method for detecting change in a pair of sequential images. The method includes training a feature descriptor based on a generated training set of matching and non-matching image pairs. An imaging subsystem captures a pair of substantially sequential images of a field of view. The pair of captured images is aligned and then transformed into corresponding arrays of patches. A matching and non-matching probability is determined for each pair of adjacent patches based on the feature descriptor. Each pair of patches is classified as matching or non-matching based on a comparison of the matching and non-matching probability. A mask is generated identifying the pairs of patches that indicate change and then displayed overlaid on at least one of the sequential images to indicate change on a user interface.

A method and a system for determining a 6-DOF-pose of an object in space use at least one marker attached to the object and a plurality of cameras. Perspectives of the cameras are directed to a common measuring space in which the object is positioned. At least one camera from the plurality of cameras is movable such that the movable camera can be adjusted with respect to the object. At least one of the cameras captures an image of said marker attached to the object. Based on the at least one captured image, spatial parameters representing the 3D-position or the 6-DOF-pose of the marker and, consequently, the 6-DOF-pose of the object in space can be determined.

A firearm system includes a firearm and a computer. Electronics in the firearm determine data that includes a pathway between different points of aim of the firearm as the firearm moves. The computer receives this data and builds an image of the pathway between the different points of aim of the firearm.

The system and method of removing burn-in from full motion video (FMV) imagery. In some cases, the technique is a pre-processing step in a forensic or military application. The system and method identify one or more burn-in overlay areas in a full motion video image and creates a mask of the one or more burn-in overlay areas. Matched intensities are created for a plurality of pixels in a mask. In some cases, in-painting is used in a center portion of the full motion video image and order-filtering in used on a periphery of the full motion video image to create the matched intensities.

Techniques for tracing back a projectile to the projectile origin are described. A method includes detecting projectile track(s) in image(s). Each projectile track crosses multiple pixels in each image. The projectile track(s) correspond to projectile(s). The projectile track(s) in the image(s) are translated to traceback path(s). The traceback path includes a known location and a projectile origin (e.g. the location at which the projectile originated, also termed the shooter's location).

Search points in a search space may be projected onto images from cameras imaging different parts of the search space. Subimages, corresponding to the projected search points, may be selected and processed to determine if a target object has been detected. Based on subimages in which target objects are detected, as well as orientation data from cameras capturing images from which the subimages were selected, positions of the target objects in the search space may be determined.