Here Global B.v.

Zichen Li

David Doria

Xin Chen

Andi Zang

Charles Morcom

Coby Spolin Parker

A method for road surface detection includes receiving ranging data including a plurality of ranging data points, extracting one or more ranging data points lying within a height range from the plurality of ranging data points, dividing the one or more ranging data points into one or more grid cells, setting a first horizontal position of a first cell point of a first grid cell of the one or more grid cells as being centered on the first grid cell, setting a first vertical position of the first cell point, and detecting the road surface based on the first vertical position and first horizontal position of the first cell point.

Road surface detection

Apparatus and methods are described for roadway lane line detection. An aerial image including a plurality of pixels is received and provides to a classification model. The classification model provides probability values assigned to at least a portion of the plurality of pixels. A comparison of the probability values is performed to select at least one pixel according to the comparison. A lane line object is identified for the selected at least one pixel.

Road modeling from overhead imagery

The present embodiments provide for automatically detecting the location and severity of occluded regions within input data. A grid representation of a scene is generated from a data set, characterizing spaces of the grid representation as free, occupied, and hidden/occluded. The grid is bounded, and a connected component analysis is performed on the hidden space to identify the occluded regions.

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Evanston, IL, United States of America

Zichen Li