ESTIMATING DISTANCE TO AN OBJECT USING A SEQUENCE OF IMAGES RECORDED BY A MONOCULAR CAMERA

• US 20160098839A1
• Filed: 12/14/2015
• Published: 04/07/2016
• 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
• Granted Patent: US 10,127,669 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• 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 computerized method for monitoring headway to an object, the method performable in a computerized system including a camera operatively connectable to a processor, wherein the processor is configured to capture in real time a plurality of image frames from the camera, wherein the camera is configured to acquire an image frame including an image of the object within a field of view of the camera, the method comprising:

detecting a horizontal edge to sub-pixel accuracy by identifying an edge of a shadow of the object on a road surface from the sun or from self illumination;

locating in the image frame an imaged height of the horizon; and

determining the headway from the vertical position of said horizontal edge relative to the imaged height of the horizon.

2. The computerized method of claim 1, further comprising:

mapping grayscale levels or grayscale gradients of a plurality of pixels in at least one of said image frames, thereby classifying said picture elements as imaging a portion of a road surface or not imaging a portion of a road surface.

3. The computerized method of claim 1, further comprising:

refining the location of the imaged height of the horizon by a technique selected from the group consisting of;

(i) measuring the shape of the imaged road,

(ii) detecting the vanishing point from at least one road marking selected from the group consisting of;

lane structure, lane marking, and horizontal line marking;

(iii) detecting relative motion of imaged points and velocity of the moving vehicle,

(iv) compensating for pitch angle variations of the camera, and

(v) detecting ego motion of the camera.

4. The computerized method of claim 1, further comprising:

tracking over time, thereby detecting in at least two image frames the horizontal edge in the respective images of the object;

based on said detecting, computing a smoothed dimension of the object by smoothing in time a measurement of said horizontal edge over the respective images of the object; and

monitoring the headway in real time by comparing an instantaneous measured dimension of the object to said smoothed measurement of the object.

5. The computerized method, according to claim 4, wherein said computing includes calculating recursively said dimension using a Kalman filter.

6. The computerized method of claim 4, wherein the object is a second vehicle and wherein said dimension is a width as measured in images of said second vehicle.

7. The computerized method of claim 1, wherein the headway is determined solely from information derived from the images.

8. A computerized system mountable in a moving vehicle, the system including a camera operatively connected to a processor, wherein the processor is configured to capture in real time a plurality of image frames from the camera including respectively a plurality of images of an object within a field of view of the camera, wherein the system is configured to monitor headway in real time to the object, wherein the processor is configured to:

detect a horizontal edge to sub-pixel accuracy by identifying an edge of a shadow of the object on a road surface from the sun or from self illumination;

locate in the image frame an imaged height of the horizon; and

determine the headway from the vertical position of said horizontal edge relative to the imaged height of the horizon.

9. The computerized system of claim 8, wherein the processor is further configured to map grayscale levels of a plurality of pixels in at least one of said image frames to classify said picture elements as imaging a portion of a road surface or not imaging a portion of a road surface.

10. The computerized system of claim 8, wherein the processor is further configured to:

refine the location of the imaged height of the horizon by a technique selected from the group consisting of;

(i) measuring the shape of the imaged road,

(ii) detecting the vanishing point from at least one road marking selected from the group consisting of;

lane structure, lane marking, and horizontal line marking;

(iii) detecting relative motion of imaged points and velocity of the moving vehicle,

(iv) compensating for pitch angle variations of the camera, and

(v) detecting ego motion of the camera.

11. The computerized system of claim 8, wherein the processor is further configured to:

track over time to detect in at least two image frames the horizontal edge in the respective images of the object;

compute a smoothed dimension of the object by smoothing in time a measurement of said horizontal edge over the respective images of the object; and

monitor the headway in real time by comparing an instantaneous measured dimension of the object to the smoothed measurement of the object.

12. The computerized system of claim 11, wherein the processor is further configured to:

perform the computation of the smoothed dimension by calculating recursively said dimension using a Kalman filter.

13. The computerized system of claim 11, wherein the object is a second vehicle and wherein said dimension is a width as measured in images of said second vehicle.

14. The computerized system of claim 8, wherein the headway is determined solely from information derived from the images.