Tracking a vehicle using an unmanned aerial vehicle

• US 10,521,665 B2
• Filed: 12/20/2017
• Issued: 12/31/2019
• Est. Priority Date: 08/06/2012
• Status: Active Grant

• Current Assignee: Cloudparc, Inc.
• Original Assignee: Cloudparc, Inc.
• Inventors: Nerayoff, Steven David, Wong, Thompson S.
• Primary Examiner(s): Patel, Shardul D
• Application Number:
  US15/849,530
• Publication Number:
  US 20180137356A1
• Time in Patent Office: 741 Days
• Field of Search: 701 3, 701408, 701514, 700276, 348148, 348149, 706 45, 382103
• 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 an object using an unmanned aerial vehicle is disclosed. A plurality of images showing the object is received from a camera of the unmanned aerial vehicle. A first static characteristic, a second static characteristic, a first dynamic characteristic, and a second dynamic characteristic of the object are determined. The second static characteristic is compared to the first static characteristic, and the second dynamic characteristic is compared to the first dynamic characteristic. It is determined that the second static characteristic is approximately equal to the first static characteristic, and that the second dynamic characteristic is approximately equal to the first dynamic characteristic. Finally, it is determined that the object is moving.

Claims

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

receiving a plurality of images showing the object from a camera of the unmanned aerial vehicle;

determining, based on one of the plurality of images, a first static characteristic of the object;

determining, based on another of the plurality of images, a second static characteristic of the object;

determining, based on two or more of the plurality of images, a first dynamic characteristic of the object;

determining, based on another two or more of the plurality of images, a second dynamic characteristic of the object;

comparing the second static characteristic to the first static characteristic;

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

comparing the second dynamic characteristic to the first dynamic characteristic;

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

determining, in response to the approximate equivalence between the second static characteristic and the first static characteristic and the approximate equivalence between the second dynamic characteristic and the first dynamic characteristic, that the object is moving,

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

2. The method of claim 1, wherein the first static characteristic and the second static characteristic are characteristics of the object that are constant over time.

3. The method of claim 2, wherein the first static characteristic and the second static characteristic are each one or more of a color, an outline, a size, and a dimension of the object.

4. The method of claim 2, wherein the object is a vehicle, and the first static characteristic and the second static 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, and a vehicle dimension.

5. The method of claim 1, wherein the first dynamic characteristic and the second dynamic characteristic are characteristics of the object that change over time.

6. The method of claim 5, wherein the first dynamic characteristic and the second dynamic characteristic are each one or more of a speed of travel and a direction of travel of the object.

7. The method of claim 5, wherein the object is a vehicle, and the first dynamic characteristic and the second dynamic characteristic are each one or more of a lane identifier, a direction, a ground speed, and an acceleration of the vehicle.

8. The method of claim 1, wherein:

the plurality of images also show a roadway or a walkway, and

the roadway or walkway is a street, a highway, a parking garage, a parking lot, an intersection, a crosswalk, a sidewalk, a pedestrian crossing, a driveway, an island, a median, or a bicycle lane.

9. The method of claim 8, wherein determining that the object is moving comprises determining that the object is traversing a portion of the roadway or the walkway.

10. The method of claim 1, further comprising determining, based on one of the plurality of images, an identifier of the object.

11. The method of claim 10, wherein the object is a vehicle, and the identifier of the 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 vehicle.

12. The method of claim 1, wherein the plurality of images also shows a vehicle, and the object is an occupant of a vehicle, the method further comprising:

determining, based on two or more of the plurality of images, that the occupant is walking to or from the vehicle; and

associating the occupant with the vehicle.

13. The method of claim 12, wherein:

the plurality of images also show a payment station of a third-party parking payment system, and

determining that the occupant is walking to or from the vehicle comprises determining that the occupant traveled between the vehicle and the payment station of the third-party parking payment system.

14. The method of claim 13, further comprising:

receiving, from the third-party parking payment system, payment information specifying a period of time that was received by the third-party parking payment system,

wherein associating the occupant with the vehicle comprises associating, in response to the determination that the occupant traveled between the vehicle and the payment station, the period of time with the vehicle.

15. The method of claim 13, wherein the third-party parking payment system is a third-party pay-by-space parking payment system, a third-party pay-and-display parking payment system, or a third-party curbside parking meter payment system.

16. The method of claim 1, wherein the object is a first object, and the plurality of images also shows a plurality of other objects.

17. The method of claim 1, further comprising providing real-time tracking of the object to a law enforcement or security system.

18. The method of claim 1, wherein each of the plurality of images includes a visual timestamp indicating a time at which the respective image was captured.

19. A system for tracking an object 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 a plurality of images showing the object from a camera of the unmanned aerial vehicle;

determine, based on one of the plurality of images, a first static characteristic of the object;

determine, based on another of the plurality of images, a second static characteristic of the object;

determine, based on two or more of the plurality of images, a first dynamic characteristic of the object;

determine, based on another two or more of the plurality of images, a second dynamic characteristic of the object;

compare the second static characteristic to the first static characteristic;

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

compare the second dynamic characteristic to the first dynamic characteristic;

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

determine, in response to the approximate equivalence between the second static characteristic and the first static characteristic and the approximate equivalence between the second dynamic characteristic and the first dynamic characteristic, that the object is moving.

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

receive a plurality of images showing the object from a camera of the unmanned aerial vehicle;

determine, based on one of the plurality of images, a first static characteristic of the object;

determine, based on another of the plurality of images, a second static characteristic of the object;

determine, based on two or more of the plurality of images, a first dynamic characteristic of the object;

determine, based on another two or more of the plurality of images, a second dynamic characteristic of the object;

compare the second static characteristic to the first static characteristic;

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

compare the second dynamic characteristic to the first dynamic characteristic;

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

determine, in response to the approximate equivalence between the second static characteristic and the first static characteristic and the approximate equivalence between the second dynamic characteristic and the first dynamic characteristic, that the object is moving.