Here Global B.v.

Engin Burak Anil

David Doria

Fangning He

Charles Morcom

Matthew Emery Goss

Nezih Ergin Ozkucur

An apparatus for sign detection includes a point cloud analysis module, an image analysis module, a frustum comparison module, and a sign detector. The point cloud analysis module is configured to receive point cloud data associated with a geographic region and classify at least one point neighborhood in the point cloud data as planar and a sign position candidate. The image analysis module is configured to receive image data associated with the geographic region and calculate a sighting frustum from the image data. The frustum comparison module is configured to perform a comparison of the sighting frustum to the sign position candidate having at least one point neighborhood classified as planar. The sign detector is configured to provide a location for the sign detection in response to the comparison of the sighting frustum to the sign position candidate.

Automatic positioning of 2D image sign sightings in 3D space

An apparatus and method automatically detects and positions structure faces. After receiving data points describing a geographical area, neighborhoods are defined based on the data points and classified as linear, planar, or volumetric. Neighborhoods are merged into at least one cluster based on local surface normals. At least one bounding frame is fit to the at least one cluster and modified based on a field of interest.

Automatic detection and positioning of structure faces

Embodiments include apparatus and methods for automatic detection of pole-like objects for a location at a region of a roadway and automatic localization based on the detected pole-like objects. Pole-like objects are modeled as cylinders and the models are generated based on detected vertical clusters of point cloud data associated to corresponding regions along the region of the roadway. The modeled pole-like objects are stored in a database and associated with the region of the roadway. Sensor data from a user located at the region of the roadway is received. The pole-like object model is accessed and compared to the received sensor data. Based on the comparison, localization of the user located at the region of the roadway is performed.

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Mount Prospect, IL, United States of America

Engin Burak Anil