Methods and systems for camera to ground alignment

1. A method for a vehicle, the method comprising:

receiving image data defining a plurality of images associated with an environment of the vehicle;

determining, by a processor, feature points within at least one image of the plurality of images;

selecting, by the processor, a subset of the feature points as ground points;

determining, by the processor, a ground plane based on the subset of feature points;

determining, by the processor, a ground normal vector from the ground plane;

determining, by the processor, the ground normal vector based on a sliding widow method, wherein the sliding window method comprises minimizing a computed transfer distance over a sliding window;

determining, by the processor, a camera to ground alignment value based on the ground normal vector; and

generating, by the processor, second image data based on the camera to ground alignment value.

2. The method of claim 1 , wherein the determining the feature points is based on a velocity of the vehicle associated with the image and an epiploar line within the image.

3. The method of claim 1 , wherein the determining the feature points is based on a velocity of the vehicle associated with the image and a vanishing point within the image.

4. The method of claim 1 , wherein the selecting the subset of feature points is based on a dynamic two dimensional image road mask.

5. The method of claim 1 , wherein the selecting the subset of feature points is based on homography constraints.

6. The method of claim 5 , wherein the lighting data includes at least one of environmental lighting data, climate data, and time of day data.

7. The method of claim 1 , further comprising:

receiving lighting data indicating lighting conditions associated with the environment of the vehicle;

selecting at least one region of interest within the at least one image based on the lighting data; and

wherein the determining the features points is based on the at least one region of interest.

8. The method of claim 1 , further comprising:

evaluating vehicle conditions to determine when the vehicle driving smooth and straight; and

wherein in response to the determination that the vehicle is driving smooth and straight, the determining the feature points is performed.

9. The method of claim 8 , wherein the vehicle conditions include vehicle acceleration, vehicle velocity, and steering wheel angle.

10. The method of claim 8 , wherein the vehicle conditions include a determined distance travelled between two images of the plurality of images.

11. The method of claim 1 , further comprising:

determining a camera pose to be unreliable based on a reference camera rotation and a translation;

filtering feature points for images with a camera pose determined to be unreliable; and

wherein the determining the subset of feature points is based on the filtered feature points.

12. The method of claim 1 , wherein the determining the ground plane is based on constraints associated with a reference ground normal vector and a vehicle motion direction.

13. A computer implemented system for a vehicle, the system comprising:

a data storage element comprising computer readable instructions; and

a processor configured to execute the computer readable instructions, the computer readable instructions controlling the processor to perform operations comprising:

receiving image data defining a plurality of images associated with an environment of the vehicle;

determining feature points within at least one image of the plurality of images;

selecting a subset of the feature points as ground;

determining a ground plane based on the subset of feature points;

determining a ground normal vector from the ground plane;

determining the ground normal vector based on a sliding widow method, wherein the sliding window method comprises minimizing a computed transfer distance over a sliding window;

determining a camera to ground alignment value based on the ground normal vector; and

generating second image data based on the camera to ground alignment value.

14. The system of claim 13 , wherein the determining the feature points is based on a velocity of the vehicle associated with the image and an epiploar line within the image.

15. The system of claim 13 , wherein the determining the feature points is based on a velocity of the vehicle associated with the image and a vanishing point within the image.

16. The system of claim 13 , wherein the selecting the subset of feature points is based on a dynamic two dimensional image road mask.

17. The system of claim 13 , wherein the selecting the subset of feature points is based on homography constraints.

18. A vehicle, comprising:

a camera configured to capture images of an environment of the vehicle; and

a controller having a processor configured to receive the images, determine feature points within at least one image, select a subset of the feature points as ground points, determine a ground plane based on the subset of feature points, determine a ground normal vector from the ground plane, determine the ground normal vector based on a sliding widow method, wherein the sliding window method comprises minimizing a computed transfer distance over a sliding window, and determine a camera to ground alignment value based on the ground normal vector.

19. The vehicle of claim 18 , wherein the determining the feature points is based on a velocity of the vehicle associated with the image and an epiploar line within the image.

20. The vehicle of claim 18 , wherein the determining of the feature points is based on a velocity of the vehicle associated with the image and a vanishing point within the image.