TRACKING A VEHICLE USING AN UNMANNED AERIAL VEHICLE

• US 20170039424A1
• Filed: 10/22/2016
• Published: 02/09/2017
• Est. Priority Date: 08/06/2012
• Status: Active Grant

• Current Assignee: Cloudparc, Inc.
• Original Assignee: Cloudparc, Inc.
• Inventors: NERAYOFF, Steven David, Wong, Thompson S.
• Granted Patent: US 9,858,480 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: B64C 39/024 of the remote controlled vehicle type, i.e. RPV
• CPC Class Codes: B64U 2101/30 for imaging, photography or videography
• CPC Class Codes: B64U 2101/31 for surveillance
• CPC Class Codes: G05D 1/0094 involving pointing a payload, e.g. camera, weapon, sensor, towards a fixed or moving target
• CPC Class Codes: G06F 18/22 Matching criteria, e.g. proximity measures
• CPC Class Codes: G06Q 20/02 involving a neutral party, e.g. certification authority, notary or trusted third party [TTP]
• CPC Class Codes: G06Q 20/145 Payments according to the detected use or quantity
• CPC Class Codes: G06Q 30/0284 Time or distance, e.g. usage of parking meters or taximeters
• CPC Class Codes: G06Q 30/04 Billing or invoicing
• CPC Class Codes: G06Q 50/265 Personal security, identity or safety
• CPC Class Codes: G06T 2207/10032 Satellite or aerial image; Remote sensing
• CPC Class Codes: G06T 2207/30244 Camera pose
• CPC Class Codes: G06T 2207/30256 Lane; Road marking
• CPC Class Codes: G06T 2207/30264 Parking
• CPC Class Codes: G06T 7/248 involving reference images or patches
• CPC Class Codes: G06T 7/32 using correlation-based methods
• CPC Class Codes: G06T 7/74 involving reference images or patches
• CPC Class Codes: G06V 20/182 Network patterns, e.g. roads or rivers
• CPC Class Codes: G06V 20/52 Surveillance or monitoring of activities, e.g. for recognising suspicious objects recognising microscopic objects G06V20/69
• CPC Class Codes: G06V 20/54 of traffic, e.g. cars on the road, trains or boats
• CPC Class Codes: G06V 20/56 : exterior to a vehicle by using sensors mounted on the vehicle
• CPC Class Codes: G06V 20/593 : Recognising seat occupancy
• CPC Class Codes: G06V 20/62 : Text, e.g. of license plates, overlay texts or captions on TV images
• CPC Class Codes: G06V 20/625 : License plates
• CPC Class Codes: G06V 30/224 : of printed characters having additional code marks or containing code marks
• CPC Class Codes: G06V 40/23 : Recognition of whole body movements, e.g. for sport training
• CPC Class Codes: G07B 15/00 : Arrangements or apparatus for collecting fares, tolls or entrance fees at one or more control points handling coins or valuable papers, e.g. banknotes, G07D; apparatus for vending or hiring articles or services activated by coins, credit cards, paper currency or the like G07F7/00, G07F17/00
• CPC Class Codes: G07B 15/02 : taking into account a variable factor such as distance or time, e.g. for passenger transport, parking systems or car rental systems G07B15/06 takes precedence; taximeters G07B13/00; parking meters per se G07F17/24; car rental systems per se G07B15/00
• CPC Class Codes: G08G 1/0175 : by photographing vehicles, e.g. when violating traffic rules
• CPC Class Codes: G08G 1/052 : with provision for determining speed or overspeed speed measuring in general G01P
• CPC Class Codes: G08G 1/056 : with provision for distinguishing direction of travel
• CPC Class Codes: G08G 1/133 : within the vehicle ; Indicators inside the vehicles or at stops
• CPC Class Codes: G08G 1/142 : external to the vehicles
• CPC Class Codes: G08G 1/143 : inside the vehicles
• CPC Class Codes: G08G 1/144 : on portable or mobile units, e.g. personal digital assistant [PDA]
• CPC Class Codes: G08G 1/148 : Management of a network of parking areas
• CPC Class Codes: G08G 5/0069 : specially adapted for an unmanned aircraft
• CPC Class Codes: H04N 23/62 : Control of parameters via user interfaces
• CPC Class Codes: H04N 23/66 : Remote control of cameras or camera parts, e.g. by remote control devices
• CPC Class Codes: H04N 23/69 : Control of means for changing angle of the field of view, e.g. optical zoom objectives or electronic zooming
• CPC Class Codes: H04N 23/80 : Camera processing pipelines; Components thereof
• CPC Class Codes: H04N 7/18 : Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast
• CPC Class Codes: H04N 7/181 : for receiving images from a plurality of remote sources

Abstract

Tracking a vehicle using an unmanned aerial vehicle is disclosed. One or more first images may be received from a first camera of the first unmanned aerial vehicle located at a first location. A parking violation committed by a first vehicle may be determined in at least one of the one or more first images. The first unmanned aerial vehicle may be then repositioned. One or more second images having the second field of view and showing the first vehicle may then be received. A unique identifier of the first vehicle may then be determined based on at least one of the one or more second images.

Claims

1. A method of tracking a vehicle using an unmanned aerial vehicle, the method comprising:

receiving, at a first time, one or more first images from a first camera of a first unmanned aerial vehicle located at a first location, the one or more first images having a first field of view and showing a first vehicle;

determining, based on at least one of the one or more first images, a first characteristic of the first vehicle;

determining, based on at least one of the one or more first images, that the first vehicle has committed a violation;

causing repositioning, in response to the determination that the first vehicle has committed the violation, of the first unmanned aerial vehicle from the first location to a second location, the second location being different from the first location;

receiving, at a second time that is after the first time, one or more second images from the first camera of the first unmanned aerial vehicle, the one or more second images having a second field of view and showing the first vehicle, the second field of view being different from the first field of view;

determining, based on at least one of the one or more second images, a second characteristic of the first vehicle;

comparing the second characteristic of the first vehicle to the first characteristic of the first vehicle;

determining, in response to the comparison of the second characteristic of the first vehicle to the first characteristic of the first vehicle, that the second characteristic of the first vehicle is approximately equal to the first characteristic of the first vehicle;

determining, in response to the approximate equivalence of the second characteristic of the first vehicle and the first characteristic of the first vehicle, that the first vehicle is present in the one or more second images;

determining, based on at least one of the one or more second images, a unique identifier of the first vehicle; and

indicating the unique identifier,

wherein the steps of receiving, determining, causing repositioning, comparing and identifying are performed by one or more processors.

2. The method of claim 1, wherein causing repositioning of the first unmanned aerial vehicle from the first location to the second location comprises:

determining a dynamic characteristic of the first vehicle; and

determining, based on the dynamic characteristic of the first vehicle, the second location of the first unmanned aerial vehicle.

3. The method of claim 2, wherein the dynamic characteristic of the first vehicle is at least one of a lane identifier, a direction, a ground speed, and an acceleration of the first vehicle.

4. The method of claim 2, wherein determining the second location of the first unmanned aerial vehicle comprises estimating a location of the first vehicle at the second time based on the dynamic characteristic of the first vehicle.

5. The method of claim 2, wherein determining the second location of the first unmanned aerial vehicle comprises determining a location of the unique identifier of the first vehicle at the second time based on the dynamic characteristic of the first vehicle.

6. The method of claim 1, wherein causing repositioning of the first unmanned aerial vehicle from the first location to the second location comprises:

determining the second location of the first unmanned aerial vehicle; and

forwarding instructions to the first unmanned aerial vehicle to reposition to the second location.

7. The method of claim 1, wherein the violation is a parking violation.

8. The method of claim 7, wherein determining that the first vehicle has committed the parking violation comprises determining, based on at least one of the one or more first images, that the first vehicle is parked at an expired parking meter.

9. The method of claim 7, wherein determining that the first vehicle has committed the parking violation comprises determining, based on at least one of the one or more first images, that the first vehicle is parked in at least one of an unauthorized parking space, a restricted parking space, a reserved parking space, a sidewalk, and a fire lane.

10. The method of claim 7, wherein determining that the first vehicle has committed the parking violation comprises determining, based on at least one of the one or more first images, that the first vehicle is blocking another vehicle.

11. The method of claim 7, wherein determining that the first vehicle has committed the parking violation comprises determining, based on at least one of the one or more first images, that the first vehicle does not display a parking permit or does not have a valid parking permit.

12. The method of claim 1, wherein the unique identifier of the first vehicle is a license plate number, a one-dimensional bar code, a matrix bar code, a parking permit identification number, a disabled placard identification number, or a vehicle registration tag associated with the first vehicle.

13. The method of claim 1, further comprising:

receiving, at a third time before the first time, one or more third images from a second camera, the one or more third images having a third field of view and showing the first vehicle, and the third field of view being different from and at least partially overlapping with the first field of view;

determining an overlap area that defines the overlap between the one or more first images and the one or more third images; and

determining a handoff zone within the overlap area, wherein tracking of the first vehicle is passed from the second camera to the first camera after the first vehicle enters the handoff zone.

14. The method of claim 13, wherein the second camera is located on a second unmanned aerial vehicle different from the first unmanned aerial vehicle.

15. The method of claim 1, wherein causing repositioning of the first unmanned aerial vehicle from the first location to the second location having the second field of view comprises:

determining a first path to the second location from the first location;

determining that an obstruction is present along the first path; and

determining, in response to the determination that the obstruction is present along the first path, a second path to the second location from the first location that does not overlap with the obstruction, the second path being different from the first path.

16. The method of claim 1, wherein:

the first characteristic and the second characteristic are each one or more of a vehicle make, a vehicle model, a vehicle year, a vehicle color, a vehicle outline, a vehicle size, a vehicle dimension of the first vehicle, a lane identifier, a direction, a ground speed, and an acceleration of the first vehicle.

17. The method of claim 1, wherein the one or more first images show at least one destination location, the method further comprising:

determining, based on at least one of the one or more first images, that the first vehicle is stopped within the at least one destination location at the first time.

18. The method of claim 1, further comprising:

receiving, at a third time that is after the second time, one or more third images from the first camera of the first unmanned aerial vehicle, the one or more third images having a third field of view and showing the first vehicle and at least one destination location;

determining, based on at least one of the one or more third images, that the first vehicle has left the at least one destination location at the third time;

indicating that the first vehicle began use of the at least one destination location at the first time;

indicating that the first vehicle completed use of the at least one destination location at the third time; and

determining a cost for the first vehicle to occupy the at least one destination location from the first time to the third time.

19. A system for tracking a vehicle using an unmanned aerial vehicle, the system comprising one or more processors connected to at least one storage device, the system being configured to:

receive, at a first time, one or more first images from a first camera of a first unmanned aerial vehicle located at a first location, the one or more first images having a first field of view and showing a first vehicle;

determine, based on at least one of the one or more first images, a first characteristic of the first vehicle;

determine, based on at least one of the one or more first images, that the first vehicle has committed a parking violation;

cause repositioning, in response to the determination that the first vehicle has committed the parking violation, of the first unmanned aerial vehicle from the first location to a second location, the second location being different from the first location;

receive, at a second time that is after the first time, one or more second images from the first camera of the first unmanned aerial vehicle, the one or more second images having a second field of view and showing the first vehicle, the second field of view being different from the first field of view;

determine, based on at least one of the one or more second images, a second characteristic of the first vehicle;

compare the second characteristic of the first vehicle to the first characteristic of the first vehicle;

determine, in response to the comparison of the second characteristic of the first vehicle to the first characteristic of the first vehicle, that the second characteristic of the first vehicle is approximately equal to the first characteristic of the first vehicle;

determine, in response to the approximate equivalence of the second characteristic of the first vehicle and the first characteristic of the first vehicle, that the first vehicle is present in the one or more second images;

determine, based on at least one of the one or more second images, a unique identifier of the first vehicle; and

indicate the unique identifier.

20. A storage device storing a computer program for tracking a vehicle using an unmanned aerial vehicle, the computer program comprising one or more code segments that, when executed, cause one or more processors to:

receive, at a first time, one or more first images from a first camera of a first unmanned aerial vehicle located at a first location, the one or more first images having a first field of view and showing a first vehicle;

determine, based on at least one of the one or more first images, a first characteristic of the first vehicle;

determine, based on at least one of the one or more first images, that the first vehicle has committed a parking violation;

cause repositioning, in response to the determination that the first vehicle has committed the parking violation, of the first unmanned aerial vehicle from the first location to a second location, the second location being different from the first location;

receive, at a second time that is after the first time, one or more second images from the first camera of the first unmanned aerial vehicle, the one or more second images having a second field of view and showing the first vehicle, the second field of view being different from the first field of view;

determine, based on at least one of the one or more second images, a second characteristic of the first vehicle;

compare the second characteristic of the first vehicle to the first characteristic of the first vehicle;

determine, in response to the comparison of the second characteristic of the first vehicle to the first characteristic of the first vehicle, that the second characteristic of the first vehicle is approximately equal to the first characteristic of the first vehicle;

determine, in response to the approximate equivalence of the second characteristic of the first vehicle and the first characteristic of the first vehicle, that the first vehicle is present in the one or more second images;

determine, based on at least one of the one or more second images, a unique identifier of the first vehicle; and

indicate the unique identifier.