Image processing method for detecting objects using relative motion

• US 9,547,795 B2
• Filed: 01/20/2012
• Issued: 01/17/2017
• Est. Priority Date: 04/25/2011
• Status: Active Grant

• Current Assignee: Magna Electronics Incorporated (Magna International Incorporated)
• Original Assignee: Magna Electronics Incorporated (Magna International Incorporated)
• Inventors: Gupta, Nikhil
• Primary Examiner(s): Bali, Vikkram
• Assistant Examiner(s): Mangialaschi, Tracy
• Application Number:
  US14/113,415
• Publication Number:
  US 20140169627A1
• Time in Patent Office: 1,824 Days
• Field of Search: None
• US Class Current: 1/1
• CPC Class Codes: B60R 2300/8093 for obstacle warning
• CPC Class Codes: G06F 18/22 Matching criteria, e.g. proximity measures
• CPC Class Codes: G06T 2207/30241 Trajectory
• CPC Class Codes: G06T 2207/30256 Lane; Road marking
• CPC Class Codes: G06T 2207/30261 Obstacle
• CPC Class Codes: G06T 5/80 Geometric correction
• CPC Class Codes: G06T 7/13 Edge detection
• CPC Class Codes: G06T 7/246 using feature-based methods, e.g. the tracking of corners or segments
• CPC Class Codes: G06T 7/248 involving reference images or patches
• CPC Class Codes: G06T 7/74 involving reference images or patches
• CPC Class Codes: G06T 7/80 Analysis of captured images to determine intrinsic or extrinsic camera parameters, i.e. camera calibration
• CPC Class Codes: G06V 20/58 Recognition of moving objects or obstacles, e.g. vehicles or pedestrians; Recognition of traffic objects, e.g. traffic signs, traffic lights or roads
• CPC Class Codes: G06V 20/588 Recognition of the road, e.g. of lane markings; Recognition of the vehicle driving pattern in relation to the road
• CPC Class Codes: G06V 20/64 Three-dimensional objects
• CPC Class Codes: H04N 7/183 for receiving images from a single remote source

Abstract

An image based obstacle detection method. A camera mounted on a vehicle provides a set of image frames while the vehicle is in motion. The image frames define an image plane having a vertical aspect and a horizontal aspect. The relevancy of an object is determined by (i) selecting first and second feature points from the object that are spaced apart vertically in a first image frame; (ii) tracking the positions of the first and second feature points over at least a second image frame; and (iii) deciding the object to be relevant if the first and second feature points move dissimilar distances in physical space, within a tolerance, and deciding the object to be irrelevant otherwise. The motion of relevant objects is then estimated to determine if any relevant object is likely to become an obstacle to the vehicle.

Claims

1. An obstacle detection method, comprising:

(a) provisioning a vehicle with a camera having an external field of view, the camera having an imager defining an image plane having a vertical aspect and a horizontal aspect, wherein the imager comprises an array of sensing pixels;

(b) acquiring a set of image frames captured by the camera while the vehicle is in motion;

(c) determining an object present in the set of captured image frames by edge detection;

(d) determining a relevancy of the determined object by

(i) selecting first and second feature points of the determined object that are spaced apart vertically in a first captured image frame,

(ii) tracking positions of the first and second feature points of the determined object over at least a second captured image frame, and

(iii) determining that the determined object is a relevant object responsive to a determination that the first and second feature points move dissimilar distances in physical space between the first and second captured image frames and within a tolerance;

(e) estimating motion of determined relevant objects relative to the vehicle to determine if any determined relevant object is likely to become an obstacle to the vehicle;

wherein step (d)(iii) is determined by reference to the image plane and, where the first feature point is vertically lower than the second feature point, and wherein the method includes;

estimating, from the first captured image frame, a physical distance D₁ of the first feature point O_1b to the camera in a selected physical horizontal plane;

estimating, from the first captured image frame, a physical location D_T of the second feature point O_1T assuming that the second feature point physically lies at a height T above the selected physical horizontal plane;

estimating, from the second captured image frame, a physical distance D₂ of the first feature point O_2b to the camera in the selected physical horizontal plane, and determining the distance Δ

D between D₂ and D₁;

estimating a physical location D*_T which is equivalent to D_T+Δ

D, with D*_T being located at a height T above the selected physical horizontal plane;

computing a nominal feature point coordinate O*_2t in the image plane corresponding to D*_T; and

determining that the determined object is the relevant object responsive to a determination that the absolute distance between the nominal feature point coordinate O*_2t and the second feature point coordinate in the first captured image frame O_1T is less than the absolute distance between the second feature point coordinate in the second captured image frame O_2T and the second feature point coordinate in the first captured image frame O_1T.

2. A method according to claim 1, wherein step (d)(iii) is determined by reference to physical space and includes:

determining first and second physical locations along a selected physical horizontal plane corresponding to pixel positions of the first and second feature points in the first captured image frame;

determining third and fourth physical locations along the selected real horizontal plane corresponding to pixel positions of the first and second feature points in the second captured image frame;

determining a first distance Δ

d1 between the third and first physical locations and determining a second distance Δ

d2 between the fourth and second physical locations; and

determining that the determined object is the relevant object responsive to a determination that the difference between the first distance Δ

d1 and the second distance Δ

d2 exceeds a threshold, and otherwise determining that the determined object is not a relevant object.

3. A method according to claim 2, including unwarping a given pixel position to account for lens distortion prior to determining a physical location corresponding to the given pixel position.

4. A method according to claim 3, wherein the first and second feature points are portions of top and bottom edge contours of the determined object.

5. A method according to claim 1, wherein the selected physical horizontal plane is a ground plane.

6. A method according to claim 5, including unwarping a given pixel position to account for lens distortion prior to determining a physical location corresponding to the given pixel position.

7. A method according to claim 6, wherein the first and second feature points are portions of top and bottom edge contours of the determined object.

8. An obstacle detection system for a vehicle, comprising:

a camera mounted at the vehicle, the camera capturing a set of image frames while the vehicle is in motion, the camera comprising an imager defining an image plane having a vertical aspect and a horizontal aspect, wherein the imager comprises an array of sensing pixels;

a controller coupled to the camera, the controller configured to determine an object in the captured image frames and determine a relevancy of the determined object by

(i) selecting first and second feature points on the determined object that are spaced apart vertically in a first captured image frame,

(ii) tracking positions of the first and second feature points over at least a second captured image frame, and

(iii) determining that the determined object is a relevant object responsive to a determination that the first and second feature points move dissimilar distances in physical space and within a tolerance, and otherwise determining that the determined object is not a relevant object; and

the controller estimating relative motion of determined relevant objects to determine if any relevant object is likely to become an obstacle to the vehicle; and

the controller providing an indication to a driver of the vehicle of determined obstacles;

wherein the controller determines the relevancy of the determined object by reference to the image plane and, where the first feature point is vertically lower than the second feature point, the controller;

estimates, from the first captured image frame, a physical distance D₁ of the first feature point O_1b to the camera in a selected physical horizontal plane;

estimates, from the first captured image frame, a physical location D_T of the second feature point O_1T assuming that the second feature point physically lies at a height T above the selected physical horizontal plane;

estimates, from the second captured image frame, a physical distance D₂ of the first feature point O_2b to the camera in the selected physical horizontal plane, and determines the distance Δ

D between D₂ and D₁;

estimates a physical location D*_T which is equivalent to D_T+Δ

D, with D*_T being located at a height T above the selected physical horizontal plane;

computes a nominal feature point coordinate O*_2t in the image plane corresponding to D*_T; and

determines the determined object to be the relevant object responsive to a determination that the absolute distance between the nominal feature point coordinate O*_2t and the second feature point coordinate in the first captured image frame O_1T is less than the absolute distance between the second feature point coordinate in the second captured image frame O_2T and the second feature point coordinate in the first captured image frame O_1T.

9. An obstacle detection system according to claim 8, wherein the controller determines the relevancy of the determined object by reference to physical space, and wherein the controller is configured to:

determine first and second physical locations along a selected physical horizontal plane corresponding to pixel positions of the first and second feature points in the first captured image frame;

determine third and fourth physical locations along the selected real horizontal plane corresponding to pixel positions of the first and second feature points in the second captured image frame;

determine a first distance Δ

d1 between the third and first physical locations and determining a second distance Δ

d2 between the fourth and second physical locations; and

determine that the determined object is the relevant object if the difference between the first distance Δ

d1 and the second distance Δ

d2 exceeds a threshold, and otherwise determining that the determined object is not a relevant object.

10. An obstacle detection system according to claim 9, wherein the controller de-warps a given pixel position to account for lens distortion prior to determining a physical location corresponding to the given pixel position.

11. An obstacle detection system according to claim 10, wherein the first and second feature points are portions of top and bottom edge contours of the determined object.

12. An obstacle detection system according to claim 9, wherein the selected physical horizontal plane is a ground plane.

13. An obstacle detection system according to claim 12, wherein the controller de-warps a given pixel position to account for lens distortion prior to determining a physical location corresponding to the given pixel position.

14. An obstacle detection system according to claim 13, wherein the first and second feature points are portions of top and bottom edge contours of the determined object.