Abstract: Described are street level intelligence platforms, systems, and methods that can include a fleet of swarm vehicles having imaging devices. Images captured by the imaging devices can be used to produce and/or be integrated into maps of the area to produce high-definition maps in near real-time. Such maps may provide enhanced street level intelligence useful for fleet management, navigation, traffic monitoring, and/or so forth.

Abstract: Described are street level intelligence platforms, systems, and methods that can include a fleet of swarm vehicles having imaging devices. Images captured by the imaging devices can be used to produce and/or be integrated into maps of the area to produce high-definition maps in near real-time. Such maps may provide enhanced street level intelligence useful for fleet management, navigation, traffic monitoring, and/or so forth.

Abstract: Described are street level intelligence platforms, systems, and methods that can include a fleet of swarm vehicles having imaging devices. Images captured by the imaging devices can be used to produce and/or be integrated into maps of the area to produce high-definition maps in near real-time. Such maps may provide enhanced street level intelligence useful for fleet management, navigation, traffic monitoring, and/or so forth.

Abstract: Described are street level intelligence platforms, systems, and methods that can include a fleet of swarm vehicles having imaging devices. Images captured by the imaging devices can be used to produce and/or be integrated into maps of the area to produce high-definition maps in near real-time. Such maps may provide enhanced street level intelligence useful for fleet management, navigation, traffic monitoring, and/or so forth.

Abstract: Computer-implemented methods and systems of detecting curbs include receiving a cloud of three-dimensional (3D) data points acquired along street locations. A plurality of vertical scanlines (e.g., arrays of 3D data points obtained at given horizontal locations) are identified within the cloud of 3D data points. One or more curb points indicating the potential presence of a curb in the plurality of vertical scanlines are identified. A synthesized set of non-overlapping curb curves are generated in order to close gaps between certain curb points while removing certain other outlier curb points. Successive curb curves in the synthesized set of non-overlapping curb curves are then identified as belonging to one or more curb segments.

Abstract: Described are street level intelligence platforms, systems, and methods that can include a fleet of swarm vehicles having imaging devices. Images captured by the imaging devices can be used to produce and/or be integrated into maps of the area to produce high-definition maps in near real-time. Such maps may provide enhanced street level intelligence useful for fleet management, navigation, traffic monitoring, and/or so forth.

Abstract: Computer-implemented methods and systems of detecting and modeling curbs include receiving a cloud of three-dimensional (3D) data points acquired along street locations. A plurality of vertical scanlines (e.g., arrays of 3D data points obtained at given horizontal locations) are identified within the cloud of 3D data points. One or more curb points indicating the potential presence of a curb in the plurality of vertical scanlines are identified. A synthesized set of non-overlapping curb curves are generated in order to close gaps between certain curb points while removing certain other outlier curb points. Successive curb curves in the synthesized set of non-overlapping curb curves are then identified as belonging to one or more curb segments. A curb model that fits each of the one or more curb segments to one or more curb model shape representations can then be generated.

Abstract: Computer-implemented methods and systems of detecting and modeling curbs include receiving a cloud of three-dimensional (3D) data points acquired along street locations. A plurality of vertical scanlines (e.g., arrays of 3D data points obtained at given horizontal locations) are identified within the cloud of 3D data points. One or more curb points indicating the potential presence of a curb in the plurality of vertical scanlines are identified. A synthesized set of non-overlapping curb curves are generated in order to close gaps between certain curb points while removing certain other outlier curb points. Successive curb curves in the synthesized set of non-overlapping curb curves are then identified as belonging to one or more curb segments. A curb model that fits each of the one or more curb segments to one or more curb model shape representations can then be generated.

Abstract: A method of establishing a cumulative sum (CUSUM) tracking strategy that limits large positions is disclosed. The method monitors the price of an asset over time and classifies changes as an upward or downward trend. An upward cumulative and downward cumulative sum are compared to thresholds. An alarm is fired when a threshold is exceeded. A buy action is performed during the upward trend or a sell action is performed during the downward trend. The method is restarted with newly-initialized upward cumulative sum and downward cumulative sum when the alarm is triggered.

Abstract: A system and related method for automatically aligning a plurality of 2D images of a scene to a first 3D model of the scene. The method includes providing a plurality of 2D images of the scene, generating a second 3D model of the scene based on the plurality of 2D images, generating a transformation between the second 3D model and the first 3D model based on a comparison of at least one of the plurality of 2D images to the first 3D model, and using the transformation to automatically align the plurality of 2D images to the first 3D model.