Online camera alignment using ensembled features from multiple views

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

one or more cameras configured to capture original images relative to the vehicle; and

a control module in communication with the camera, the control module configured to:

receive at least two original images from the one or more cameras of the vehicle;

identify at least one target feature in the original images;

select local regions of interest for the identified target feature in the original images;

load view settings for each local region of interest, the view settings for each local region of interest including at least a size and a resolution;

adjust at least one of the view settings for the local regions of interest;

create one or more synthetic local images for each original image based on the local regions of interest and the loaded view settings;

detect at least one feature in the one or more synthetic local images; and

align the camera with an object associated with the vehicle using the detected feature, wherein the object is the vehicle, the ground, or another camera of the vehicle,

wherein the control module includes a machine learning module configured to generate the view settings for each local region of interest, and the control module is configured to receive the view settings for each local region of interest from the machine learning module.

2 . The vehicle system of claim 1 , wherein the control module is configured to control an operation of the vehicle based on the alignment between the camera and the object.

3 . The vehicle system of claim 2 , wherein the operation of the vehicle includes a motion or trajectory of the vehicle.

4 . The vehicle system of claim 1 , wherein the machine learning module includes a neural network.

5 . The vehicle system of claim 1 , wherein:

the control module is configured to determine inlier ratios associated with a plurality of detected features; and

the machine learning module is configured to adjust the at least one of the view settings for the local regions of interest based on the determined inlier ratios.

6 . The vehicle system of claim 1 , wherein the control module is configured to generate a transformation matrix to map the detected feature between the synthetic local images and at least one of the original images.

7 . The vehicle system of claim 6 , wherein the control module is configured to project the target feature back to the at least one of the original images based on the transformation matrix.

8 . The vehicle system of claim 7 , wherein the transformation matrix is a homography transformation matrix.

9 . A method for aligning one or more cameras of a vehicle with an object associated with the vehicle, the method comprising:

receiving at least two original images from the one or more cameras;

identifying at least one target feature in the original images;

selecting local regions of interest for the identified target feature in the original images;

loading view settings for each local region of interest, the view settings for each local region of interest including at least a size and a resolution;

adjusting the at least one of the view settings for the local regions of interest by determining inlier ratios associated with a plurality of detected features and removing at least one of the view settings corresponding to the lowest inlier ratio of the inlier ratios:

creating one or more synthetic local images for each original image based on the local regions of interest and the loaded view settings;

detecting at least one feature in the one or more synthetic local images; and

aligning the camera with an object associated with the vehicle using the detected feature, wherein the object is the vehicle, the ground, or a second camera of the vehicle.

10 . The method of claim 9 , further comprising controlling an operation of the vehicle based on the alignment between the camera and the object.

11 . The method of claim 10 , wherein the operation of the vehicle includes a motion or trajectory of the vehicle.

12 . The method of claim 9 , wherein loading the view settings for each local region of interest includes generating, with a machine learning module, the view settings for each local region of interest.

13 . The method of claim 9 , further comprising generating a transformation matrix to map the detected feature between the synthetic local images and at least one of the original images.

14 . The method of claim 13 , further comprising projecting the target feature back to the at least one of the original images based on the transformation matrix.

15 . A vehicle system for a vehicle, the vehicle system comprising:

one or more cameras configured to capture original images relative to the vehicle; and

a control module in communication with the camera, the control module configured to:

receive at least two original images from the one or more cameras of the vehicle;

identify at least one target feature in the original images;

select local regions of interest for the identified target feature in the original images;

load view settings for each local region of interest, the view settings for each local region of interest including at least a size and a resolution;

adjust at least one of the view settings for the local regions of interest by determining inlier ratios associated with a plurality of detected features and removing at least one of the view settings corresponding to the lowest inlier ratio of the inlier ratios;

create one or more synthetic local images for each original image based on the local regions of interest and the loaded view settings;

detect at least one feature in the one or more synthetic local images; and

align the camera with an object associated with the vehicle using the detected feature, wherein the object is the vehicle, the ground, or another camera of the vehicle.

16 . The vehicle system of claim 15 , wherein the control module is configured to control an operation of the vehicle based on the alignment between the camera and the object.

17 . The vehicle system of claim 16 , wherein the operation of the vehicle includes a motion or trajectory of the vehicle.

18 . The vehicle system of claim 15 , wherein the control module is configured to generate a transformation matrix to map the detected feature between the synthetic local images and at least one of the original images.

19 . The vehicle system of claim 18 , wherein the control module is configured to project the target feature back to the at least one of the original images based on the transformation matrix.

20 . The vehicle system of claim 18 , wherein the transformation matrix is a homography transformation matrix.