Estimating distance to an object using a sequence of images recorded by a monocular camera

• US 10,127,669 B2
• Filed: 12/14/2015
• Issued: 11/13/2018
• Est. Priority Date: 01/04/2006
• Status: Active Grant

• Current Assignee: MobilEye Vision Technologies Ltd. (Intel Corporation)
• Original Assignee: MobilEye Vision Technologies Ltd. (Intel Corporation)
• Inventors: Stein, Gideon P., Ferencz, Andras D., Avni, Ofer
• Primary Examiner(s): Chang, Jungwon
• Application Number:
  US14/967,560
• Publication Number:
  US 20160098839A1
• Time in Patent Office: 1,065 Days
• Field of Search: 701 93, 701301, 701 96, 340436, 382106, 382103, 382104, 382100, 348135
• CPC Class Codes: B60R 11/04 Mounting of cameras operative during drive; Arrangement of controls thereof relative to the vehicle
• CPC Class Codes: B60R 2001/1253 with cameras, video cameras or video screens
• CPC Class Codes: B60R 2300/105 using multiple cameras
• CPC Class Codes: B60R 2300/802 for monitoring and displaying vehicle exterior blind spot views
• CPC Class Codes: B60R 2300/8093 for obstacle warning
• CPC Class Codes: G01B 11/026 by measuring distance between sensor and object G01B11/0608 takes precedence
• CPC Class Codes: G01B 11/14 for measuring distance or clearance between spaced objects or spaced apertures G01B11/26 takes precedence; rangefinders G01C3/00
• CPC Class Codes: G01C 22/00 Measuring distance traversed on the ground by vehicles, persons, animals or other moving solid bodies, e.g. using odometers, using pedometers
• CPC Class Codes: G01C 3/00 Measuring distances in line of sight; Optical rangefinders tapes, chains or wheels for measuring length G01B3/00; active triangulation systems, i.e. using the transmission and reflection of electromagnetic waves other than radio waves, G01S17/48
• CPC Class Codes: G01C 3/22 using a parallactic triangle with variable angles and a base of fixed length at, near, or formed by the object
• CPC Class Codes: G01S 11/12 using electromagnetic waves other than radio waves
• CPC Class Codes: G01S 17/93 for anti-collision purposes
• CPC Class Codes: G06T 2207/10016 Video; Image sequence
• CPC Class Codes: G06T 2207/20024 Filtering details
• CPC Class Codes: G06T 2207/30196 Human being; Person
• CPC Class Codes: G06T 2207/30252 Vehicle exterior; Vicinity of vehicle
• CPC Class Codes: G06T 2207/30256 Lane; Road marking
• CPC Class Codes: G06T 2207/30261 Obstacle
• CPC Class Codes: G06T 7/55 from multiple images
• 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

Abstract

A method for monitoring headway to an object performable in a computerized system including a camera mounted in a moving vehicle. The camera acquires in real time multiple image frames including respectively multiple images of the object within a field of view of the camera. An edge is detected in in the images of the object. A smoothed measurement is performed of a dimension the edge. Range to the object is calculated in real time, based on the smoothed measurement.

Claims

1. A system for determining a distance from a moving vehicle to an object ahead of the moving vehicle, comprising:

a processor configured to;

receive, from an image capturing device mounted on the moving vehicle, a first image including a first representation of the object, a second image including a second representation of the object, and a third image including a third representation of the object;

measure a first dimension of the first representation of the object in the first image and a second dimension of the second representation of the object in the second image;

determine an actual dimension of the object based on the measured first dimension and the measured second dimension, wherein the processor is configured to determine the actual dimension of the object by;

determining a first actual dimension based on the measured first dimension, a height of the image capturing device relative to a road surface, and a first distance from the horizontal edge to a horizontal reference line measured in the first image;

determining a second actual dimension based on the measured second dimension, the height of the image capturing device relative to the road surface, and a second distance from the horizontal edge to the horizontal reference line measured in the second image; and

determining the actual dimension based on the first actual dimension and the second actual dimension;

measure a third dimension of the third representation of the object in the third image;

determine the distance from the moving vehicle to the object based on the measured third dimension and the actual dimension; and

provide a warning to a driver of the moving vehicle based on the distance.

2. The system of claim 1, wherein the first dimension is a dimension of a first representation of a horizontal edge of the object in the first image, and the second dimension is a dimension of a second representation of the horizontal edge of the object in the second image.

3. The system of claim 2, wherein the first dimension is a width of the first representation of the horizontal edge of the object in the first image, and the second dimension is a width of the second representation of the horizontal edge of the object in the second image.

4. The system of claim 3, wherein the object is a lead vehicle ahead of the moving vehicle and the horizontal edge is a bottom edge of the lead vehicle.

5. The system of claim 3, wherein the processor is further configured to detect two vertical edges at both ends of the horizontal edge in at least one of the first and second images, and determine the widths of the horizontal edge based on a distance between the two vertical edges in at least one of the first and second images.

6. The system of claim 2, wherein the second image is received a time period after the first image is received.

7. The system of claim 6, wherein the third image is received a time period after the first and second images are received.

8. The system of claim 1, wherein the actual dimension is determined based on the first actual dimension and the second actual dimension using a Kalman filter.

9. The system of claim 1, wherein the horizontal reference line is a predetermined line in at least one image captured by the image capturing device.

10. The system of claim 1, wherein the processor is configured to determine the distance by determining the distance based on a ratio between the actual dimension and the measured third dimension, and a focal length of the image capturing device.

11. A method for determining a distance from a moving vehicle to an object ahead of the moving vehicle, comprising:

receiving, from an image capturing device, a first image including a first representation of the object, a second image including a second representation of the object, and a third image including a third representation of the object;

measuring, by a processing unit, a first dimension of first representation of the object in the first image and a second dimension of the second representation of the object in the second image;

determining, by the processing unit, an actual dimension of the object based on the measured first dimension and the measured second dimension, wherein determining the actual dimension comprises;

determining a first actual dimension based on the measured first dimension, a height of the image capturing device relative to a road surface, and a first distance from the horizontal edge to a horizontal reference line measured in the first image;

determining a second actual dimension based on the measured second dimension, the height of the image capturing device relative to the road surface, and a second distance from the horizontal edge to the horizontal reference line measured in the second image; and

determining the actual dimension based on the first actual dimension and the second actual dimension;

measuring, by the processing unit, a third dimension of the third representation of the object in the third image;

determining, by the processing unit, the distance from the moving vehicle to the object based on the measured third dimension and the actual dimension; and

providing a warning to a driver of the moving vehicle based on the distance.

12. The method of claim 11, wherein the first dimension is a dimension of a first representation of a horizontal edge of the object in the first image, and the second dimension is a dimension of a second representation of the horizontal edge of the object in the second image.

13. The method of claim 12, wherein the first dimension is a width of the first representation of the horizontal edge of the object in the first image, and the second dimension is a width of the second representation of the horizontal edge of the object in the second image.

14. The method of claim 13, wherein the object is a lead vehicle ahead of the moving vehicle and the horizontal edge is a bottom edge of the lead vehicle.

15. The method of claim 13, further comprising detecting two vertical edges at both ends of the horizontal edge in at least one of the first and second images, and determining the widths of the horizontal edge based on a distance between the two vertical edges in at least one of the first and second images.

16. The method of claim 11, wherein the second image is received a time period after the first image is received.

17. The method of claim 16, wherein the third image is received a time period after the first and second images are received.

18. The method of claim 11, wherein the actual dimension is determined based on the first actual dimension and the second actual dimension using a Kalman filter.

19. The method of claim 11, wherein the horizontal reference line is a predetermined line in at least one image captured by the image capturing device.

20. The method of claim 11, wherein determining the distance comprises determining the distance based on a ratio between the actual dimension and the measured third dimension and a focal length of the image capturing device.