Abstract: Described is a system for analyzing time series data. A sequence of symbols is generated from a set of time series input data related to a moving vehicle using automatic segmentation. A grammar is extracted from the sequence of symbols, and the grammar is a subset of a probabilistic context-free grammar (PCFG). Using the grammar, time series input data can be analyzed, and a prediction of the vehicle's movement can be made. Vehicle operations for an autonomous vehicle are determined using the prediction.

Abstract: Described is a system for analyzing time series data. A sequence of symbols is generated from a set of time series input data related to a moving vehicle using automatic segmentation. A grammar is extracted from the sequence of symbols, and the grammar is a subset of a probabilistic context-free grammar (PCFG). Using the grammar, time series input data can be analyzed, and a prediction of the vehicle's movement can be made. Vehicle operations for an autonomous vehicle are determined using the prediction.

Abstract: The present application generally relates to a method and apparatus for generating an action policy for controlling an autonomous vehicle. In particular, the method is operative to receive an input indicative of a training event, segmenting the driving episode into a plurality of time steps, generate a parse tree in response to each time step, and generate a most probable parse tree from a combination of the generated parse trees.

Abstract: A method for automatic target recognition in synthetic aperture radar (SAR) data, comprising: capturing a real SAR image of a potential target at a real aspect angle and a real grazing angle; generating a synthetic SAR image of the potential target by inputting, from a potential target database, at least one three-dimensional potential target model at the real aspect angle and the real grazing angle into a SAR regression renderer; and, classifying the potential target with a target label by comparing at least a portion of the synthetic SAR image with a corresponding portion of the real SAR image using a processor.

Abstract: The present application generally relates to a method and apparatus for generating an action policy for controlling an autonomous vehicle. In particular, the method is operative to receive an input indicative of a training event, segmenting the driving episode into a plurality of time steps, generate a parse tree in response to each time step, and generate a most probable parse tree from a combination of the generated parse trees.

Abstract: A method and apparatus for recognizing target objects. The method comprises identifying a group of target objects in an image. Further, the method comprises forming a group of chips encompassing the group of target objects identified in the image. Yet further, the method comprises recognizing the group of target objects in the group of chips using a group of filters, wherein the group of filters was created using a group of models for reference objects and environmental information for a location where the group of target objects was located when the image was generated, wherein a filter in the group of filters comprises a group of reference images for a reference object in the reference objects.

Abstract: A method for automatic target recognition in synthetic aperture radar (SAR) data, comprising: capturing a real SAR image of a potential target at a real aspect angle and a real grazing angle; generating a synthetic SAR image of the potential target by inputting, from a potential target database, at least one three-dimensional potential target model at the real aspect angle and the real grazing angle into a SAR regression renderer; and, classifying the potential target with a target label by comparing at least a portion of the synthetic SAR image with a corresponding portion of the real SAR image using a processor.

Abstract: A method and apparatus for processing video data streams for an area. Objects are identified in the area from images in the video data streams. The video data streams are generated by cameras. First locations are identified for the objects using the images. The first locations are defined using a coordinate system for the images. Graphical representations are formed for the objects using the images. The graphical representations are displayed for the objects in second locations in a model of the area on a display system with respect to features in the area that are represented in the model. The second locations are defined using a geographic coordinate system for the model. A first location in the first locations for an object in the objects corresponds to a second location in the second locations for a corresponding graphical representation in the graphical representations.

Abstract: A motion detector comprising a sensor apparatus and a calculator arranged for: generating first and second successive frames comprising each a 3-D cloud of points, wherein each point represents a position in space of a surface of at least an object in the field of vision of said sensor apparatus; transforming each of the first and second frames by: mapping each cloud of 3-D points into a 2-D grid of cells associated each to a sequence of predetermined volumes; and associating to each cell of the 2-D grid of cells a sequence of the lists of the points contained in corresponding volumes of the sequence of predetermined volumes; comparing the sequences of lists associated to the same cells of the 2-D grids obtained for the first and second frames; and indicating that motion occurred based on the sequence of lists being different in the first and second frames.

Abstract: A method for detecting an opening in a structure represented by a three-dimensional point cloud may include the steps of: (1) creating a three-dimensional point cloud map of a scene, the three-dimensional point cloud map including a plurality of points representing a ground plane and the structure upon the ground plane, (2) identifying an absence of points within the plurality of points representing the structure, and (3) determining whether the absence of points represents the opening in the structure.

Abstract: A method for detecting an opening in a structure represented by a three-dimensional point cloud may include the steps of: (1) creating a three-dimensional point cloud map of a scene, the three-dimensional point cloud map including a plurality of points representing a ground plane and the structure upon the ground plane, (2) identifying an absence of points within the plurality of points representing the structure, and (3) determining whether the absence of points represents the opening in the structure.

Abstract: A method and target detector for detecting targets. A number of bright pixels are identified in an image. Each of the number of bright pixels belongs to a line detected in the image in which the line represents a candidate for a target. A number of feature vectors are identified for the number of bright pixels in the image. Each of the number of feature vectors is classified as one of a target vector representing the target and a clutter vector representing clutter.

Abstract: A method and apparatus for processing video data streams for an area. Objects are identified in the area from images in the video data streams. The video data streams are generated by cameras. First locations are identified for the objects using the images. The first locations are defined using a coordinate system for the images. Graphical representations are formed for the objects using the images. The graphical representations are displayed for the objects in second locations in a model of the area on a display system with respect to features in the area that are represented in the model. The second locations are defined using a geographic coordinate system for the model. A first location in the first locations for an object in the objects corresponds to a second location in the second locations for a corresponding graphical representation in the graphical representations.