Abstract: In various examples, object fence corresponding to objects detected by an ego-vehicle may be used to determine overlap of the object fences with lanes on a driving surface. A lane mask may be generated corresponding to the lanes on the driving surface, and the object fences may be compared to the lanes of the lane mask to determine the overlap. Where an object fence is located in more than one lane, a boundary scoring approach may be used to determine a ratio of overlap of the boundary fence, and thus the object, with each of the lanes. The overlap with one or more lanes for each object may be used to determine lane assignments for the objects, and the lane assignments may be used by the ego-vehicle to determine a path or trajectory along the driving surface.

Abstract: In various examples, object fence corresponding to objects detected by an ego-vehicle may be used to determine overlap of the object fences with lanes on a driving surface. A lane mask may be generated corresponding to the lanes on the driving surface, and the object fences may be compared to the lanes of the lane mask to determine the overlap. Where an object fence is located in more than one lane, a boundary scoring approach may be used to determine a ratio of overlap of the boundary fence, and thus the object, with each of the lanes. The overlap with one or more lanes for each object may be used to determine lane assignments for the objects, and the lane assignments may be used by the ego-vehicle to determine a path or trajectory along the driving surface.

Abstract: In various examples, object fence corresponding to objects detected by an ego-vehicle may be used to determine overlap of the object fences with lanes on a driving surface. A lane mask may be generated corresponding to the lanes on the driving surface, and the object fences may be compared to the lanes of the lane mask to determine the overlap. Where an object fence is located in more than one lane, a boundary scoring approach may be used to determine a ratio of overlap of the boundary fence, and thus the object, with each of the lanes. The overlap with one or more lanes for each object may be used to determine lane assignments for the objects, and the lane assignments may be used by the ego-vehicle to determine a path or trajectory along the driving surface.

Abstract: In various examples, object fence corresponding to objects detected by an ego-vehicle may be used to determine overlap of the object fences with lanes on a driving surface. A lane mask may be generated corresponding to the lanes on the driving surface, and the object fences may be compared to the lanes of the lane mask to determine the overlap. Where an object fence is located in more than one lane, a boundary scoring approach may be used to determine a ratio of overlap of the boundary fence, and thus the object, with each of the lanes. The overlap with one or more lanes for each object may be used to determine lane assignments for the objects, and the lane assignments may be used by the ego-vehicle to determine a path or trajectory along the driving surface.

Abstract: A method, system, and medium for automated analysis of business intelligence each: receive natural language input from a user; evaluate, via a natural language understanding processor that includes a parser and an interpreter, the natural language input to determine an intent of the user; determine the intent of the user and generate a query based on a context manager; send an identification of the failure to a failure analysis system for human intervened analysis and refinement of a natural language model used by the natural language understand processor; assess, via a context manager processor, to determine a user interest in one or more portions of results of the query, a scrolling of the user through the results of the query; and refine, based on the user interest in the one or more portions of the results of the query, an output of the results of the query.

Abstract: A method, system, and medium for automated analysis of business intelligence each: receive natural language input from a user; evaluate, via a natural language understanding processor that includes a parser and an interpreter, the natural language input to determine an intent of the user; determine the intent of the user and generate a query based on a context manager; send an identification of the failure to a failure analysis system for human intervened analysis and refinement of a natural language model used by the natural language understand processor; assess, via a context manager processor, to determine a user interest in one or more portions of results of the query, a scrolling of the user through the results of the query; and refine, based on the user interest in the one or more portions of the results of the query, an output of the results of the query.

Abstract: An embodiment of the present invention is directed to a user friendly dynamic tool for business intelligence automated analytics that enable end users, e.g., employees, etc. to maximize efficiency and flexibility while interacting with data systems across applications. An embodiment of the present invention provides real-time analytics based on Artificial Intelligence (AI) and an interactive Chatbot interface. The innovative framework may be applicable across various lines of business and scenarios.

Abstract: In various examples, object fence corresponding to objects detected by an ego-vehicle may be used to determine overlap of the object fences with lanes on a driving surface. A lane mask may be generated corresponding to the lanes on the driving surface, and the object fences may be compared to the lanes of the lane mask to determine the overlap. Where an object fence is located in more than one lane, a boundary scoring approach may be used to determine a ratio of overlap of the boundary fence, and thus the object, with each of the lanes. The overlap with one or more lanes for each object may be used to determine lane assignments for the objects, and the lane assignments may be used by the ego-vehicle to determine a path or trajectory along the driving surface.

Abstract: In various examples, object fence corresponding to objects detected by an ego-vehicle may be used to determine overlap of the object fences with lanes on a driving surface. A lane mask may be generated corresponding to the lanes on the driving surface, and the object fences may be compared to the lanes of the lane mask to determine the overlap. Where an object fence is located in more than one lane, a boundary scoring approach may be used to determine a ratio of overlap of the boundary fence, and thus the object, with each of the lanes. The overlap with one or more lanes for each object may be used to determine lane assignments for the objects, and the lane assignments may be used by the ego-vehicle to determine a path or trajectory along the driving surface.

Abstract: In various examples, object fence corresponding to objects detected by an ego-vehicle may be used to determine overlap of the object fences with lanes on a driving surface. A lane mask may be generated corresponding to the lanes on the driving surface, and the object fences may be compared to the lanes of the lane mask to determine the overlap. Where an object fence is located in more than one lane, a boundary scoring approach may be used to determine a ratio of overlap of the boundary fence, and thus the object, with each of the lanes. The overlap with one or more lanes for each object may be used to determine lane assignments for the objects, and the lane assignments may be used by the ego-vehicle to determine a path or trajectory along the driving surface.

Abstract: In various examples, object fence corresponding to objects detected by an ego-vehicle may be used to determine overlap of the object fences with lanes on a driving surface. A lane mask may be generated corresponding to the lanes on the driving surface, and the object fences may be compared to the lanes of the lane mask to determine the overlap. Where an object fence is located in more than one lane, a boundary scoring approach may be used to determine a ratio of overlap of the boundary fence, and thus the object, with each of the lanes. The overlap with one or more lanes for each object may be used to determine lane assignments for the objects, and the lane assignments may be used by the ego-vehicle to determine a path or trajectory along the driving surface.

Abstract: An embodiment of the present invention is directed to a user friendly dynamic tool for business intelligence automated analytics that enable end users, e.g., employees, etc. to maximize efficiency and flexibility while interacting with data systems across applications. An embodiment of the present invention provides real-time analytics based on Artificial Intelligence (AI) and an interactive Chatbot interface. The innovative framework may be applicable across various lines of business and scenarios.

Abstract: A method for displaying a live preview image on a mobile device is disclosed. The method includes computing a history color value and confidence value for each pixel of a sensor of a camera. Further, it includes obtaining a new frame of pixels from the camera. Subsequently, for each pixel in the new frame, the method includes: (a) determining if a pixel color is similar to a corresponding history color value and if a confidence corresponding to a pixel is above a predetermined threshold; (b) if the pixel color is not similar to the history color value and the confidence is above the predetermined threshold, displaying the history color value on the preview when displaying the new frame; and (c) if the pixel color is similar to the history color value or the confidence is below the threshold, displaying the pixel color on the preview instead.

Abstract: A method for tracking device orientation on a portable device is disclosed. The method comprises initializing a device orientation to a sensor orientation, wherein the sensor orientation is based on information from an inertial measurement unit (IMU) sensor. It also comprises initiating visual tracking using a camera on the portable device and capturing a frame. Next, it comprises determining a plurality of visual features in the frame and matching the frame to a keyframe, wherein capture of the keyframe precedes capture of the frame. Subsequently, it comprises computing a rotation amount between the frame and the keyframe. Responsive to a determination that a rotational distance between the frame and the keyframe exceeds a predetermined threshold, promoting the frame to a keyframe status and adding it to a first orientation map and adjusting the frame with all prior captured keyframes.

Abstract: A method for displaying a live preview image on a mobile device is disclosed. The method comprises computing a history color value and confidence value for each pixel of a sensor of a camera on the device. Further, it comprises obtaining a new frame of pixels from the camera. Subsequently, for each pixel in the new frame, the method comprises: (a) determining if a pixel color is similar to a corresponding history color value and if a confidence corresponding to a pixel is above a predetermined threshold; (b) if the pixel color is not similar to the history color value and the confidence is above the predetermined threshold, displaying the history color value on the preview when displaying the new frame; and (c) if the pixel color is similar to the history color value or the confidence is below the threshold, displaying the pixel color on the preview instead.