Traffic Monitoring

• US 20100231720A1
• Filed: 09/03/2008
• Published: 09/16/2010
• Est. Priority Date: 09/05/2007
• Status: Abandoned Application

• Current Assignee: TRW Limited (Zeppelin - Stiftung der Stadt Friedrichshafen)
• Original Assignee: TRW Limited (Zeppelin - Stiftung der Stadt Friedrichshafen)
• Inventors: Tucker, Mark Richard, Reeve, John Martin
• Application Number:
  US12/676,279
• Publication Number:
  US 20100231720A1
• Time in Patent Office: Days
• US Class Current: 348/149
• CPC Class Codes: G06T 2207/10016 Video; Image sequence
• CPC Class Codes: G06T 2207/30236 Traffic on road, railway or crossing
• CPC Class Codes: G06T 7/20 Analysis of motion motion estimation for coding, decoding, compressing or decompressing digital video signals H04N19/43, H04N19/51
• CPC Class Codes: G06T 7/60 Analysis of geometric attributes
• CPC Class Codes: G06V 10/255 Detecting or recognising potential candidate objects based on visual cues, e.g. shapes
• CPC Class Codes: G06V 20/54 of traffic, e.g. cars on the road, trains or boats
• CPC Class Codes: G06V 2201/08 Detecting or categorising vehicles
• CPC Class Codes: G08G 1/0104 Measuring and analyzing of parameters relative to traffic conditions
• CPC Class Codes: G08G 1/015 with provision for distinguishing between two or more types of vehicles, e.g. between motor-cars and cycles
• CPC Class Codes: G08G 1/0175 by photographing vehicles, e.g. when violating traffic rules

Abstract

A method of monitoring traffic on a road comprising capturing a plurality of images of the road using a camera mounted on a viewing point and associating a time of capture with each image, determining, from the captured images, the positions of the portions of the road surface visible from the viewpoint at the front and rear extremities of the extent of a vehicle in the captured images at two different times; and determining from the positions and the times of the instants at least one characteristic of the vehicle or its motion, such as the vehicle length, speed or a vehicle classification (truck, car, motorcycle, etc).

Claims

1. A method of monitoring traffic on a road comprising the steps of:

capturing a plurality of images of the road using a camera mounted on a viewing point and associating a time of capture with each image,

determining, from said captured plurality of images, the positions of the portions of the road surface visible from said viewpoint corresponding to a front extremity and a rear extremity of the extent of a vehicle in said plurality of the captured images at two different times; and

determining from said positions and the times of said different times at least one characteristic of said vehicle or its motion.

2. The method of claim 1, wherein the characteristics of the vehicle or its motion include at least one of the vehicle length, height, width and speed.

3. The method of claim 12, wherein the determinations are made for the times when the vehicle blocks a view from the camera of a first line across said road and a second line across said road, the first and second lines being spaced from one another along said road;

and when the first line and said second line are revealed due to passage of the vehicle along the road.

4. The method of claim 3, wherein the first line and second line are visible features on said road surface.

5. The method of claim 3, wherein the method also includes a step of assigning areas of road surface within the field of view of the camera as the first and second lines.

6. The method of claim 3, wherein the characteristics include vehicle speed and the method includes determining a speed of the vehicle using the time elapsed between the blocking and revealing of at least one of the first and second lines, combined with a measurement of a distance between the first and second lines.

7. The method of claim 3, wherein the height of the vehicle is calculated as:

$h=H<br><br><br><br>\frac{\mathrm{\Delta <br><br>}<br><br><br><br>\mathrm{tf}-\mathrm{\Delta <br><br>}<br><br><br><br>\mathrm{tr}}{\mathrm{\Delta <br><br>}<br><br><br><br>\mathrm{tf}},$

where;

h is the vehicle height,

H is the height above the road surface that the camera is mounted,

Δ

tf is the time elapsed between the closest edge of the vehicle to the camera in the field of view traversing the first and second lines, and

Δ

tr is the time elapsed between the farthest edge of the vehicle to the camera in the field of view traversing the first and second lines.

8. The method of claim 3, wherein the length of the vehicle is calculated as:

$l=\frac{\mathrm{xf}<br><br><br><br>1·<br><br>\mathrm{\Delta <br><br>}<br><br><br><br>t<br><br><br><br>2-\mathrm{xf}<br><br><br><br>2·<br><br>\mathrm{\Delta <br><br>}<br><br><br><br>t<br><br><br><br>1}{\mathrm{\Delta <br><br>}<br><br><br><br>\mathrm{tf}},$

where;

l is the length of the vehicle,

Δ

t1 is the time elapsed between the first line being blocked and revealed,

Δ

t2 is the time elapsed between the second line being blocked and revealed,

Δ

tf is the time elapsed between the vehicle blocking the first and second lines,

xf1 is the distance from the point on the road directly underneath the camera to the first line, and

xf2 is the distance from the point on the road directly underneath the camera to the second line.

9. The method of claim 1, wherein the times for which the positions are calculated may be the times at which the two images are captured.

10. The method of claim 9, further including capturing the first of said two images at a time when the vehicle is in a first zone within the field of view of the camera, and then waiting until the vehicle enters a second zone of the field of view before designating the second image as such.

11. The method of claim 9, wherein the speed of the vehicle is calculated according to:

$V=\frac{\mathrm{\Delta <br><br>}<br><br><br><br>\mathrm{xf}}{\mathrm{\Delta <br><br>}<br><br><br><br>t},$

where;

Δ

xf is the change in distance from the camera along the road of the closest extremity of the vehicle to the camera, and

Δ

t is the time elapsed between the two times.

12. The method of claim 9, wherein the height of the vehicle is calculated according to:

$l=\frac{\mathrm{xf}<br><br><br><br>1·<br><br>\mathrm{xr}<br><br><br><br>2-\mathrm{xf}<br><br><br><br>2·<br><br>\mathrm{xr}<br><br><br><br>1}{\mathrm{xf}<br><br><br><br>1-\mathrm{xr}<br><br><br><br>2},$

where;

xf1 is the distance along the road from a point directly underneath the camera to the closest edge of the vehicle in a first one of the two images,

xf2 is the distance along the road from the point directly underneath the camera to the closest edge of the vehicle in a second one of the two images,

xr1 is the distance along the road from the point directly underneath the camera to the point on the road visible next to the farthest edge of the vehicle in the first of the two images, and

xr2 is the distance along the road from the point directly underneath the camera to the point on the road visible next to the farthest edge of the vehicle in the second of the two images.

13. The method of claim 9, wherein the height of the vehicle is calculated according to:

$h=H<br><br>\left(1-\frac{\mathrm{xf}<br><br><br><br>1-\mathrm{xf}<br><br><br><br>2}{\mathrm{xr}<br><br><br><br>1-\mathrm{xr}<br><br><br><br>2}\right),$

where;

H is the height of the camera above the road,

xf1 is the distance along the road from a point directly underneath the camera to the closest edge of the vehicle in a first one of the two images,

xf2 is the distance along the road from the point directly underneath the camera to the closest edge of the vehicle in a second one of the two images,

xr1 is the distance along the road from the point directly underneath the camera to the point on the road visible next to the farthest edge of the vehicle in the first of the two images, and

xr2 is the distance along the road from the point directly underneath the camera to the point on the road visible next to the farthest edge of the vehicle in the second of the two images.

14. The method of claim 1, wherein the step of determining the position of the portions of the road surface visible at the extremities of the vehicle includes determining the shape of the road surface and using the shape of the road surface to transform a position within the image into a physical position on the road.

16. The method of claim 1, further including the step of applying a temporal high pass filter to the images, so that only fast changes in the images are considered.

17. The method of claim 3, further including determining the width of the vehicle dependent upon the amount of the line that is blocked by the vehicle.

18. The method of claim 3, further including the step of counting vehicles crossing one of the first and second lines.

34. The method of claim 1 further including a step that occurs prior to the listed steps, the prior occurring step including providing a suitable processor and a data carrier, the data carrier carrying processor instructions which, when loaded into the processor, cause the processor to carry out the subsequent steps of the method.

15. (canceled)

19. A traffic monitoring apparatus, comprising:

a camera having an output and arranged so as to, in use, capture images and to output the captured images at the output,

a processing unit, coupled to the output of the camera and arranged to, in use, analyse the captured images, the processing unit including a position determination unit arranged to take as its input a plurality of images of a road and a vehicle travelling along the road captured by the camera, the plurality of images being taken of the road at different times, the time of capture of each image being associated with that image, the processing unit also arranged to output the positions of the portions of the road surface visible from the camera at the front and rear extremities of the extent of the vehicle in the captured images at two different times; and

a characteristic determining unit arranged to take as an input the positions and the times of the instants, the characteristic determining unit also arranged to output at least one characteristic of the vehicle or its motion.

20. The apparatus of claim 19, wherein the characteristics of the vehicle or its motion comprise at least one of the vehicle length, height, width and speed.

21. The apparatus of claim 19, wherein the position determining unit is arranged to determine the times when the vehicle blocks the view from the camera of a first line across the road and a second line across the road, the first and second lines being spaced from one another along the road;

and when the first and second lines are revealed due to passage of the vehicle along the road.

22. The apparatus of claim 21, wherein the processing unit also includes a memory arranged to record in use the assignment of areas of road surface within the field of view of the camera as the first and second lines.

23. The apparatus of claim 21, wherein the characteristic determining unit is arranged to determine the vehicle speed using the time elapsed between the blocking and revealing of at least one of the first and second lines.

24. The apparatus of claim 21, wherein the characteristic determining unit is arranged to determine the height of the vehicle as:

$h=H<br><br><br><br>\frac{\mathrm{\Delta <br><br>}<br><br><br><br>\mathrm{tf}-\mathrm{\Delta <br><br>}<br><br><br><br>\mathrm{tr}}{\mathrm{\Delta <br><br>}<br><br><br><br>\mathrm{tf}},$

where;

h is the vehicle height, H is the height above the road surface that the camera is mounted,

Δ

tf is the time elapsed between the closest edge of the vehicle to the camera in the field of view traversing the first and second lines, and

Δ

tr is the time elapsed between the farthest edge of the vehicle to the camera in the field of view traversing the first and second lines.

25. The apparatus of claim 21, wherein the characteristic determining unit is arranged to determine the length of the vehicle as:

$l=\frac{\mathrm{xf}<br><br><br><br>1·<br><br>\mathrm{\Delta <br><br>}<br><br><br><br>t<br><br><br><br>2-\mathrm{xf}<br><br><br><br>2·<br><br>\mathrm{\Delta <br><br>}<br><br><br><br>t<br><br><br><br>1}{\mathrm{\Delta <br><br>}<br><br><br><br>\mathrm{tf}},$

where;

l is the length of the vehicle, Δ

t1 is the time elapsed between the first line being blocked and revealed,

Δ

t2 is the time elapsed between the second line being blocked and revealed,

Δ

tf is the time elapsed between the vehicle blocking the first and second lines,

xf1 is the distance from the point on the road directly underneath the camera to the first line, and

xf2 is the distance from the point on the road directly underneath the camera to the second line.

26. The apparatus of claim 19, wherein the position determining unit is arranged so as to calculate the positions for the times at which two images are captured.

27. The apparatus of claim 26, wherein the position determining unit is arranged to take, as an input, a first of the two images from when the vehicle is in a first zone within the field of view of the camera, and a second image from when the vehicle is in the a second zone of the field of view.

28. The apparatus of claim 26, wherein the characteristic determining unit is arranged to determine the speed of the vehicle according to:

$V=\frac{\mathrm{\Delta <br><br>}<br><br><br><br>\mathrm{xf}}{\mathrm{\Delta <br><br>}<br><br><br><br>t},$

where;

Δ

xf is the change in distance from the camera along the road of the closest extremity of the vehicle to the camera, and

Δ

t is the time elapsed between the two times.

29. The apparatus of claim 26, wherein the characteristic determining unit is arranged to determine the height of the vehicle according to:

$l=\frac{\mathrm{xf}<br><br><br><br>1·<br><br>\mathrm{xr}<br><br><br><br>2-\mathrm{xf}<br><br><br><br>2·<br><br>\mathrm{xr}<br><br><br><br>1}{\mathrm{xr}<br><br><br><br>1-\mathrm{xr}<br><br><br><br>2},$

where;

xf1 is the distance along the road from a point directly underneath the camera to the closest edge of the vehicle in a first one of the two images,

xf2 is the distance along the road from the point directly underneath the camera to the closest edge of the vehicle in a second one of the two images,

xr1 is the distance along the road from the point directly underneath the camera to the point on the road visible next to the farthest edge of the vehicle in the first of the two images, and

xr2 is the distance along the road from the point directly underneath the camera to the point on the road visible next to the farthest edge of the vehicle in the second of the two images.

30. The apparatus of claim 26, wherein the characteristic determining unit is arranged to determine the height of the vehicle according to:

$h=H<br><br>\left(1-\frac{\mathrm{xf}<br><br><br><br>1-\mathrm{xf}<br><br><br><br>2}{\mathrm{xr}<br><br><br><br>1-\mathrm{xr}<br><br><br><br>2}\right),$

where;

H is the height of the camera above the road,

xf1 is the distance along the road from a point directly underneath the camera to the closest edge of the vehicle in a first one of the two images,

xf2 is the distance along the road from the point directly underneath the camera to the closest edge of the vehicle in a second one of the two images,

xr1 is the distance along the road from the point directly underneath the camera to the point on the road visible next to the farthest edge of the vehicle in the first of the two images, and

xr2 is the distance along the road from the point directly underneath the camera to the point on the road visible next to the farthest edge of the vehicle in the second of the two images.

31. The apparatus of claim 19, wherein the position determining unit is arranged so as to determine the position of the road surface visible at the extremities of the vehicle by determining the shape of the road surface and using the shape of the road surface to transform a position within the image into a physical position on the road.

32. The apparatus of claim 19, wherein the processing unit also includes a temporal high pass filter, which acts on the captured images, such that only fast changes in the images are considered by the processing unit.

33. The apparatus of claim 19, wherein the characteristic determining unit may be arranged so as to determine the width of the vehicle dependent upon the amount of each line that is blocked by the vehicle.