Abstract:
A data set may be compressed by predicting a value for the values of the data set. A comparative value may then be determined between a predicted value and an actual value for the particular points of the data set. The comparators for the particular points of the data set may then be encoded.
Abstract:
Systems, apparatuses, and methods are provided for refining building alignment in an aerial image. At least one candidate shifting vector and matching score value are determined for a local building. At least one dominant shifting vector is determined for at least one random group of neighboring buildings of the local building. At least one optimized matching score is calculated using the at least one candidate shifting vector for the local building and the at least one dominant shifting vector for the at least one random group of the neighboring buildings. A final shifting vector for the local building is found using the at least one optimized matching score.
Abstract:
A computing device performs matching between a target image and one or more template images. The computing device receives image data and performs an edge detection algorithm on the image data. The edge detection algorithm includes a distance metric based on angles between gradient vectors in the image data and gradient vectors in one or more templates. The computing device matches a building model to the image data based on results of the edge detection algorithm, wherein the building model is associated with the one or more templates.
Abstract:
Methods, apparatuses, and systems are provided for detecting overhead obstructions along a path segment. One exemplary method includes receiving three-dimensional data collected by a depth sensing device traveling along a path segment, wherein the three-dimensional data comprises point cloud data positioned above a ground plane of the path segment. The method further includes identifying data points of the point cloud data positioned within a corridor positioned above the ground plane. The method further includes projecting the identified data points onto a plane. The method further includes detecting the overhead obstruction based on a concentration of point cloud data positioned within a plurality of cells of the plane. The method further includes storing the detected overhead obstruction above the path segment within a map database.
Abstract:
Embodiments include apparatus and methods for generating a localization geometry or occupancy grid for a geographic location. Point cloud that describes a vicinity of a pathway is collected by a distance sensor and describing a vicinity of the pathway. The point cloud data is reduced or filtered to a predetermined volume with respect to the roadway. The remaining point cloud data is projected onto a two-dimensional plane including at least one pixel formation. A volumetric grid is defined according to the at least one pixel formation, and a voxel occupancy for each of a voxels forming the volumetric grid is determined. The arrangement of the voxel occupancies or a sequence of data describing the voxel occupancies is a localization geometry that describes the geographic location of the pathway.
Abstract:
An apparatus, method and computer program product are provided to facilitate the navigation of a vehicle, such as an autonomous vehicle, utilizing map data in which the quality associated with the map data is provided in a more computationally efficient manner. In the context of a method a plurality of different types of sensor data are received including map data, camera data and detector data. The method determines a quality index associated with the map data and weights the reliance upon the map data relative to other types of sensor data based upon the quality index associated with the map data. The method further includes determining navigation information for the vehicle based at least partly upon the weighting of the map data relative to other types of sensor data.
Abstract:
An apparatus comprising a processor and memory including computer program code, the memory and computer program code configured to, with the processor, enable the apparatus at least to: generate, in respect of a road intersection, grouped probe data using probe data derived from probed vehicular movements through the road intersection, wherein the grouped probe data is generated by grouping together probe data comprising vehicle trajectories which have respective common heading angles at points of entry to and exit from the road intersection; and provide the grouped probe data for use in lane-level mapping of the road intersection.
Abstract:
Embodiments include apparatus and methods for generating a localization geometry or occupancy grid for a geographic location. Point cloud that describes a vicinity of a pathway is collected by a distance sensor and describing a vicinity of the pathway. The point cloud data is reduced or filtered to a predetermined volume with respect to the roadway. The remaining point cloud data is projected onto a two-dimensional plane including at least one pixel formation. A volumetric grid is defined according to the at least one pixel formation, and a voxel occupancy for each of a voxels forming the volumetric grid is determined. The arrangement of the voxel occupancies or a sequence of data describing the voxel occupancies is a localization geometry that describes the geographic location of the pathway.
Abstract:
Methods for rendering three-dimensional photo meshes having dynamic content include: (a) detecting a shadow in a three-dimensional photo mesh; (b) removing the shadow from the three-dimensional photo mesh to form a modified photo mesh having a shadow-free texture; (c) simulating a real-time condition in the modified photo mesh; and (d) rendering an image that shows an effect of the real-time condition. Systems for rendering three-dimensional photo meshes having dynamic content are described.
Abstract:
Lane level traffic levels are determined based on traffic camera images. A controller aligns a three-dimensional map with a traffic camera view, and identifies multiple lanes in the traffic camera view based on lane delineations of the three-dimensional map. The controller calculates a traffic parameter based on the multiple lanes in image frames from the traffic camera view and provides a traffic graphic based on the traffic parameter.