Image-based risk estimation

• US 10,049,286 B2
• Filed: 12/15/2015
• Issued: 08/14/2018
• Est. Priority Date: 12/15/2015
• Status: Active Grant

• Current Assignee: NEC Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Garnavi, Rahil, Lynar, Timothy M., Sedai, Suman, Wagner, John M.
• Primary Examiner(s): Seth, Manav
• Application Number:
  US14/969,619
• Publication Number:
  US 20170169369A1
• Time in Patent Office: 973 Days
• CPC Class Codes: G01C 21/3647 Guidance involving output of stored or live camera images or video streams
• CPC Class Codes: G05D 1/0027 involving a plurality of vehicles, e.g. fleet or convoy travelling fleet control of land vehicles from a control room G05D1/0297; traffic control systems for road vehicles G08G1/00; for marine craft G08G3/00; for aircraft G08G5/00
• CPC Class Codes: G06F 11/3065 Monitoring arrangements determined by the means or processing involved in reporting the monitored data error or fault reporting or logging G06F11/0766
• CPC Class Codes: G06F 16/5854 using shape and object relationship
• CPC Class Codes: G06Q 10/0635 Risk analysis of enterprise or organisation activities
• CPC Class Codes: G06Q 10/08 Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
• CPC Class Codes: G06Q 50/265 Personal security, identity or safety
• CPC Class Codes: G06T 2207/10004 Still image; Photographic image
• CPC Class Codes: G06T 2207/30252 Vehicle exterior; Vicinity of vehicle
• CPC Class Codes: G06T 7/0002 Inspection of images, e.g. flaw detection
• CPC Class Codes: G06T 7/248 involving reference images or patches
• CPC Class Codes: G06V 10/25 Determination of region of interest [ROI] or a volume of interest [VOI]
• CPC Class Codes: G06V 20/54 of traffic, e.g. cars on the road, trains or boats
• CPC Class Codes: G06V 20/584 of vehicle lights or traffic lights
• CPC Class Codes: G06V 2201/09 Recognition of logos
• CPC Class Codes: G06V 40/172 Classification, e.g. identification

Abstract

A method, system, and computer program product to perform image-based estimation of a risk of a vehicle having a specified status include receiving images from one or more cameras, obtaining one or more vehicle images of the vehicle from the image, classifying the vehicle based on the one or more vehicle images to determine a vehicle classification, extracting features from the one or more vehicle images based on the vehicle classification, and comparing the features with risk indicators to determine estimation of the risk. Instructions are provided for an action based on the risk.

Claims

1. A computer-implemented method of performing image-based estimation of a risk of a vehicle having a specified status, the method comprising:

receiving, using a processor, images from one or more cameras;

obtaining one or more vehicle images of the vehicle from the image;

classifying the vehicle based on the one or more vehicle images to determine a vehicle classification;

extracting features from the one or more vehicle images based on the vehicle classification, wherein the features include a truck trailer, vehicle damage, a logo, a number of axels, a number of wheels, or running lights;

comparing the features with risk indicators to determine estimation of the risk; and

providing, using the processor, instructions for an action based on the risk.

2. The computer-implemented method according to claim 1, wherein the extracting the features based on the vehicle classification includes extracting the features based on the vehicle classification being a classification of interest.

3. The computer-implemented method according to claim 1, wherein the performing the image-based estimation is of the risk of the vehicle having a weight over a predetermined threshold.

4. The computer-implemented method according to claim 3, wherein the receiving the images includes receiving at least a front view, a rear view, and a side view of each of the sides of the vehicle.

5. The computer-implemented method according to claim 3, wherein the extracting the features based on the vehicle classification includes extracting the features based on the vehicle being classified as a truck.

6. The computer-implemented method according to claim 3, wherein the extracting the features from the one or more vehicle images includes extracting a license plate.

7. The computer-implemented method according to claim 3, wherein the providing the instructions based on the risk includes indicating that the vehicle must stop at a weighing station.

8. The computer-implemented method according to claim 1, further comprising storing the risk indicators based on the specified status, wherein the comparing the features with the risk indicators includes assigning a value to the estimation of the risk based on a result of the comparing.

9. A system to perform image-based estimation of a risk of a vehicle having a specified status, the system comprising:

a memory device configured to store risk indicators associated with the specified status; and

a processor configured to receive images from one or more cameras, obtain one or more vehicle images of the vehicle from the image, classify the vehicle based on the one or more vehicle images to determine a vehicle classification, extract features from the one or more vehicle images based on the vehicle classification, compare the features with the risk indicators to determine estimation of the risk, and provide instructions for an action based on the risk, wherein the features include a truck trailer, vehicle damage, a logo, a number of axels, a number of wheels, or running lights.

10. The system according to claim 9, wherein the specified status is an overweight vehicle with a weight over a predetermined threshold.

11. The system according to claim 10, wherein the processor receives the one or more vehicle images including at least a front view, a rear view, and a side view of each of the sides of the vehicle.

12. The system according to claim 10, wherein the processor extracts the features based on the vehicle being classified as a truck.

13. The system according to claim 10, wherein the processor extracts a license plate from the one or more vehicle images.

14. The system according to claim 10, wherein the processor indicates that the vehicle must stop at a weighing station based on the risk.

15. The system according to claim 9, wherein the processor assigns a value to the estimation of the risk based on a result of comparing the features with the risk indicators.

16. A computer program product for performing image-based estimation of a risk of a vehicle having a specified status, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a processor to perform a method comprising:

receiving images from one or more cameras;

obtaining one or more vehicle images of the vehicle from the image;

classifying the vehicle based on the one or more vehicle images to determine a vehicle classification;

extracting features from the one or more vehicle images based on the vehicle classification, wherein the features include a truck trailer, vehicle damage, a logo, a number of axels, a number of wheels, or running lights;

comparing the features with risk indicators to determine estimation of the risk; and

providing instructions for an action based on the risk.

17. The computer program product according to claim 16, wherein the performing the image-based estimation is of the risk of the vehicle having a weight over a predetermined threshold.

18. The computer program product according to claim 17, wherein the receiving the images includes receiving at least a front view, a rear view, and a side view of each of the sides of the vehicle, and the extracting the features based on the vehicle classification includes extracting the features based on the vehicle being classified as a truck.

19. The computer program product according to claim 17, wherein the extracting the features from the one or more vehicle images includes extracting a license plate, and the providing the instructions based on the risk includes indicating that the vehicle must stop at a weighing station.

20. The computer program product according to claim 16, further comprising storing the risk indicators based on the specified status, wherein the comparing the features with the risk indicators includes assigning a value to the estimation of the risk based on a result of the comparing.