Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.