Abstract: Subject matter regards generating a 3D point cloud and registering the 3D point cloud to the surface of the Earth (sometimes called “geo-locating”). A method can include capturing, by unmanned vehicles (UVs), image data representative of respective overlapping subsections of the object, registering the overlapping subsections to each other, and geo-locating the registered overlapping subsections.

Abstract: Subject matter regards generating a 3D point cloud and registering the 3D point cloud to the surface of the Earth (sometimes called “geo-locating”). A method can include capturing, by unmanned vehicles (UVs), image data representative of respective overlapping subsections of the object, registering the overlapping subsections to each other, and geo-locating the registered overlapping subsections.

Abstract: A system and method of generating point clouds from passive images. Image clusters are formed, wherein each image cluster includes two or more passive images selected from a set of passive images. Quality of the point cloud that could be generated from each image cluster is predicted for each image cluster based on a performance prediction score for each image cluster. A subset of image clusters is selected for further processing based on their performance prediction scores. A mission-specific quality score is determined for each point cloud generated and the point cloud with the highest quality score is selected for storage.

Abstract: A system and method of generating point clouds from passive images. Image clusters are formed, wherein each image cluster includes two or more passive images selected from a set of passive images. Quality of the point cloud that could be generated from each image cluster is predicted for each image cluster based on a performance prediction score for each image cluster. A subset of image clusters is selected for further processing based on their performance prediction scores. A mission-specific quality score is determined for each point cloud generated and the point cloud with the highest quality score is selected for storage.

Abstract: In accordance with particular embodiments, a method includes receiving LIDAR data associated with a geographic area and generating a three-dimensional image of the geographic area based on the LIDAR data. The method further includes presenting at least a first portion of the three-dimensional image to a user based on a camera at a first location. The first portion of the three-dimensional image is presented from a walking perspective. The method also includes navigating the three-dimensional image based on a first input received from the user. The first input is used to direct the camera to move along a path in the walking perspective based on the first input and the three-dimensional image. The method further includes presenting at least a second portion of the three-dimensional image to the user based on navigating the camera to a second location. The second portion of the three dimensional image presented from the walking perspective.

Abstract: A method includes obtaining image data associated with a specified area having one or more objects. The method also includes segmenting the image data into one or more segments associated with the one or more objects. The method further includes analyzing each of the one or more segments to identify a vibrometry spectrum associated with the corresponding object. In addition, the method includes generating an image of the specified area using the vibrometry spectrum associated with each object. The image of the specified area could illustrate each of the one or more objects with an intensity based on a total power of that target's total vibrational energy. The image of the specified area could also illustrate movement of at least one object over time.

Abstract: A method includes obtaining image data associated with a specified area having one or more objects. The method also includes segmenting the image data into one or more segments associated with the one or more objects. The method further includes analyzing each of the one or more segments to identify a vibrometry spectrum associated with the corresponding object. In addition, the method includes generating an image of the specified area using the vibrometry spectrum associated with each object. The image of the specified area could illustrate each of the one or more objects with an intensity based on a total power of that target's total vibrational energy. The image of the specified area could also illustrate movement of at least one object over time.

Abstract: In accordance with particular embodiments, a method includes receiving LIDAR data associated with a geographic area and generating a three-dimensional image of the geographic area based on the LIDAR data. The method further includes presenting at least a first portion of the three-dimensional image to a user based on a camera at a first location. The first portion of the three-dimensional image is presented from a walking perspective. The method also includes navigating the three-dimensional image based on a first input received from the user. The first input is used to direct the camera to move along a path in the walking perspective based on the first input and the three-dimensional image. The method further includes presenting at least a second portion of the three-dimensional image to the user based on navigating the camera to a second location. The second portion of the three dimensional image presented from the walking perspective.

Abstract: Disclosed is a system and method for predicting political instability. This instability is predicted for specific countries or geographic regions. In one embodiment, the prediction is carried out on a basis of a probabilistic model, such as a Bayesian-network. The model is comprised of various notes corresponding to dependent and independent variables. The independent variables, in turn, correspond to factors relating to historical political instability. The dependent variable corresponds to the prediction of instability. By populating the independent variables with current data, future political instability can be predicted.

Abstract: In accordance with a particular embodiment of the invention, a method for explaining a recommendation produced by a decision support tool is disclosed. The method comprises submitting a list of observation inputs to the decision support tool and producing a recommendation. The list of inputs is then reordered according to an observation metric. The method further comprises quantifying how each input impacts the probability of the recommendation produced. The inputs may then be ranked by comparing the associated changes in probability of the recommendation produced.

Abstract: In accordance with a particular embodiment of the invention, a method for explaining a recommendation produced by a decision support tool is disclosed. The method comprises submitting a list of observation inputs to the decision support tool and producing a recommendation. The list of inputs is then reordered according to an observation metric. The method further comprises quantifying how each input impacts the probability of the recommendation produced. The inputs may then be ranked by comparing the associated changes in probability of the recommendation produced.

Abstract: Apparatus and methods effective for detecting, locating and characterizing traffic-related incidents are based upon improved image processing techniques applied to infrared and visible light spectrum roadway images in a time sequence. Substantially real-time isolation and identification of anomalous or unexpected traffic conditions allows control of traffic signals and dispatch of law enforcement, maintenance or emergency medical care resources to reduce cost and increase safety. Detectable traffic-related incidents include, for example, the appearance of a stationary object on a roadway, the appearance of a pedestrian on a roadway, and the identification and location of vehicles obstructing traffic flow by moving too slowly or erratically or in the wrong direction.

Abstract: A method for measuring strain in a sample of material. A reference image is obtained of a surface of the sample. A test machine is used to apply a load to the sample, as determined by a control signal from a system processor. A measurement image is then obtained, and test points on the reference image are located on the measurement image, using an image processor programmed to perform machine vision. The displacements between the location of the test points on the two images are determined. These displacements are used to calculate strain. Each new strain value may be used by the system processor to determine a next load value, so that the load is adjusted in terms of strain parameters.