Here Global B.v.

Navteq B.v.

Victor Lu

Xin Chen

Matei Stroila

Antonio Haro

Ian Endres

Bradley Dean Kohlmeyer

Guangli Wu

Jeffrey Minoru Adachi

Masha Kamali Moghaddam

Mahsa Kamali Moghaddam

A vehicle ranging system includes a ranging scanner, a ranging data processor, and an object classifier. The ranging scanner may be configured to generate a series of ranging data. The ranging data processor may be configured to apply a scale invariant ranging template to the series of ranging data and determine a difference between the ranging template and the series of ranging data. The object classifier may be configured to identify an object corresponding to the series of ranging data based on the difference between the ranging template and the series of ranging data.

One-dimensional vehicle ranging

An approach is provided for regularizing building footprints. The approach, for example, involves designating a vertex of an initial building footprint as an initial vertex of a regularized footprint. The approach also involves generating an edge from the initial vertex to a next vertex of the initial footprint to add to the regularized footprint when that the edge can connect along a taxicab distance. The taxicab distance, for instance, is based on a rectilinear geometry between two points. The approach further involves adding a new vertex to the regularized footprint when the edge cannot connect along the taxicab distance. The edge then connects the initial vertex to the new vertex, and another edge connects the new vertex to the next vertex along the taxicab distance. The approach further involves generating a subsequent new edge or vertex of the regularized footprint for each subsequent next vertex of the initial footprint.

Method and apparatus for regularizing building footprints using taxicab distance

Embodiments described herein relate generally to determining correspondence between a template and an object in an image. A method may include: receiving an image of an environment including an image of an object within the image of the environment; resizing the first template to obtain a scaled first template having a size corresponding to a size of the image of the object; calculating a number of correspondences between the scaled first template and the image of the object; receiving a candidate homography; testing the candidate homography; and replacing the image of the object with a second template of a different object according to the candidate homography in response to the candidate homography being established as corresponding to the image of the object.

Method and apparatus for homography estimation

An approach is provided for generating a cleaned object model to represent an object in a mapping database. The approach includes receiving point cloud data depicting the object. The approach also includes processing the point cloud data to determine one or more surface points of the point cloud data. The one or more surface points represent one or more surfaces of the object. The approach further includes cutting a model of the object into one or more fragments using the one or more surface points. The one or more fragments include one or more object fragments and one or more non-object fragments. The approach further includes designating the one or more object fragments as the cleaned object model to represent the object in the mapping database.

Method and apparatus for generating a cleaned object model for an object in a mapping database

In one embodiment, image detection is improved or accelerated using an approximate range query to classify images. A controller is trained on a set of training feature vectors. The training feature vectors represent an image. The feature vectors are normalized to a uniform length. The controller defines a matching space that includes the set of training feature vectors. The controller is configured to identify whether an input vector for a tested image falls within the matching space based on a range query. When the input vector falls within the matching space, the tested image substantially matches the portion of the image used to train the controller.

Acceleration of linear classifiers

Systems, devices, features, and methods for determining geographic features corresponding to a travel path to develop a map database, such as a navigation database, are disclosed. For example, one method comprises emitting light from a light source, such as a LIDAR device, while on the travel path. Returning light is received based on the emitted light. The returning light is used to generate data points representing an area about the travel path. The data points are filtered as a function of a return intensity value to identify a feature associated with the travel path, in which the feature is treated with a retroreflective substance.

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Urbana, IL, United States of America

Victor Lu