System and method for lateral vehicle detection

1. A system comprising:

a data processor; and

a memory for storing an autonomous lateral vehicle detection system, executable by the data processor, the autonomous lateral vehicle detection system being configured to:

receive image data from at least one camera installed on an autonomous vehicle;

warp the image data based on a line parallel to an orientation of the autonomous vehicle defined with configuration parameters corresponding to an installation orientation of the at least one camera relative to the autonomous vehicle;

extract an object from the warped image data; and

apply a bounding box around the extracted object in the warped image data.

2. The system of claim 1 wherein the at least one camera comprises a plurality of cameras, wherein the autonomous lateral vehicle system is further configured to:

identify matching portions of extracted features from the warped image data from different ones of the plurality of cameras;

stitch together the warped image data based on the matching portions of the extracted features; and

form the bounding box based on the matching portions of the extracted object.

3. The system of claim 2 wherein applying the bounding box around the extracted object in the warped image data comprises:

applying portions of the bounding box respectively, on the warped image data from different ones of the plurality of cameras, wherein forming the bounding box based on the matching portions of the extracted object comprises:

stitching together the portions of the bounding box based on the matching portions of the extracted object.

4. The system of claim 1 wherein the at least one camera is at least one laterally-facing camera associated with the autonomous vehicle, wherein the at least one laterally-facing camera is from the group consisting of: a forward laterally-facing camera and a backward laterally-facing camera.

5. The system of claim 1 wherein the autonomous lateral vehicle system is further configured to

warp the image data based on a line parallel to a side of the autonomous vehicle defined with the configuration parameters.

6. The system of claim 5 wherein the line is a pre-defined line, or a line extracted from the image data.

7. The system of claim 5 wherein the line parallel to the side of the autonomous vehicle is configured based on an installation of the at least one camera, wherein the configuration parameters further correspond to an orientation of a bottom edge of the image data.

8. A method comprising:

receiving image data from at least one camera installed on an autonomous vehicle;

warping the image data based on a line parallel to an orientation of the autonomous vehicle defined with configuration parameters corresponding to an installation orientation of the at least one camera relative to the autonomous vehicle;

extracting an object from the warped image data; and

applying a bounding box around the extracted object in the warped image data.

9. The method of claim 8 wherein the warped image data creates a trapezoidal image.

10. The method of claim 8 wherein the bounding box is rectangular.

11. The method of claim 8 wherein the at least one camera comprises a plurality of cameras, wherein the method further comprises:

identifying matching portions of extracted features from the warped image data from different ones of the plurality of cameras; and

stitching together the warped image data based on the matching portions of the extracted features, wherein the stitched image data forms a single contiguous image representing a stitched image from the plurality of cameras.

12. The method of claim 11 further comprising:

forming the bounding box based on the matching portions of the extracted object.

13. The method of claim 8 wherein the at least one camera comprises a plurality of cameras, wherein the method further comprises:

identifying matching portions of extracted features from the warped image data from different ones of the plurality of cameras; and

combining the warped image data based on the matching portions of the extracted features, wherein the combined image data forms a single contiguous image representing a combined image from the plurality of cameras.

14. The method of claim 8 wherein a number of the extracted object is at least two, wherein a number of the bounding box is at least two, wherein each of the bounding boxes corresponds to each of the extracted objects respectively.

15. A non-transitory machine-useable storage medium embodying instructions which, when executed by a machine, cause the machine to:

receive image data from at least one camera installed on an autonomous vehicle;

warp the image data based on a line parallel to an orientation of the autonomous vehicle defined with configuration parameters corresponding to an installation orientation of the at least one camera relative to the autonomous vehicle;

extract an object from the warped image data; and

apply a bounding box around the extracted object in the warped image data.

16. The non-transitory machine-useable storage medium of claim 15 wherein the object in the warped image data is aligned with an orientation of the autonomous vehicle.

17. The non-transitory machine-useable storage medium of claim 15 wherein the at least one camera comprises a plurality of cameras, wherein the non-transitory machine-useable storage medium embodying instruction further causes the machine to:

stitch together the warped image data from different ones of the plurality of cameras to form a single image, wherein the bounding box is applied around the extracted object in the single image.

18. The non-transitory machine-useable storage medium of claim 17 wherein the bounding box is trapezoidal.

19. The non-transitory machine-useable storage medium of claim 17 wherein the single image is modified to be rectangular.

20. The non-transitory machine-useable storage medium of claim 15 wherein the bounding box is two-dimensional (2D).