PREDICTION VERIFICATION USING A SELF-CALIBRATING CAMERA

• US 20160349408A1
• Filed: 05/29/2015
• Published: 12/01/2016
• Est. Priority Date: 05/29/2015
• Status: Abandoned Application

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Suits, Frank
• Application Number:
  US14/725,000
• Publication Number:
  US 20160349408A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G01W 1/10 Devices for predicting weather conditions computers per se G06; display devices G09
• CPC Class Codes: G06T 2207/10016 Video; Image sequence
• CPC Class Codes: G06T 2207/30192 Weather; Meteorology
• CPC Class Codes: G06T 7/251 involving models

Abstract

A computer processor may determine a predicted object attribute for a target object by analyzing a prediction model. The camera may capture a first image and then, after some time, a second image that both contain the target object. By comparing the first and second images, the computer processor may determine a measured object attribute for the target object. The processor may then determine whether the prediction model is accurate by comparing the measured object attribute to the predicted object attribute.

Claims

1. A computer implemented method for validating a prediction model, the method comprising:

determining a predicted object attribute for a target object by analyzing a prediction model;

capturing, by a camera, a first image and a second image, the second image being captured subsequent to the first image being captured, wherein the first and second images contain the target object;

determining, by a processor, a measured object attribute for the target object by comparing the first and second images;

determining, by the processor, whether the prediction model is correct by comparing the measured object attribute to the predicted object attribute; and

validating, by the processor and in response to determining that the prediction model is correct, the prediction model.

2. The method of claim 1, wherein the target object is a cloud, the object attribute is an angular velocity, and the prediction model is a weather forecast.

3. The method of claim 2, wherein the determining a predicted object attribute comprises:

determining, from the weather forecast, a predicted cloud height;

determining, from the weather forecast, a predicted wind velocity at the predicted cloud height; and

calculating a predicted angular velocity for the cloud using the predicted wind velocity and the predicted cloud height.

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

updating, in response to determining that the prediction model is incorrect, the prediction model using the measured object attribute.

5. The method of claim 1, wherein the determining a measured object attribute for the target object comprises:

determining a first pixel location for the target object, the first pixel location corresponding to the first image;

determining a second pixel location for the target object, the second pixel location corresponding to the second image;

determining an image velocity by comparing the first pixel location and the second pixel location; and

determining the measured object attribute by applying an image transform to the image velocity.

6. The method of claim 1, the method further comprising calibrating the camera by:

capturing a third image, the third image containing two or more celestial bodies;

determining a pixel location for each of the two or more celestial bodies;

determining a known location for the two or more celestial bodies; and

calibrating the camera by comparing the pixel locations for the two or more celestial bodies to the known location for the two or more celestial bodies.

7. A system for validating a prediction model comprising:

a memory to store an image analysis module and a prediction verification module; and

a processor configured to;

run the image analysis module, wherein the image analysis module is configured to;

import, from a camera, a first image and a second image, the first and second images containing a target object; and

determine a measured object attribute for the target object by comparing the first and second images;

run the prediction verification module, wherein the prediction verification module is configured to;

determine, from a prediction model, a predicted object attribute for the target object; and

determine, in response to determining a predicted object attribute for the target object, whether the prediction model is accurate by comparing the predicted object attribute to the measured object attribute.

8. The system of claim 7, the system further comprising a digital camera.

9. The system of claim 8, wherein the digital camera includes a GPS module.

10. The system of claim 8, wherein the memory further stores a camera calibration module, and wherein the processor is further configured to run the camera calibration module.

11. The system of claim 10, wherein the camera calibration module is configured to:

capture a third image, the third image containing two or more celestial bodies;

determine a pixel location for each of the two or more celestial bodies;

determine a known location for the two or more celestial bodies; and

determine an orientation of the camera by comparing the pixel locations for the two or more celestial bodies to the known location of the two or more celestial bodies.

12. The system of claim 7, wherein the target object is a cloud, the prediction model is a weather model, and the object attribute is an angular velocity.

13. A computer program product for validating a prediction model, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, wherein the computer readable storage medium is not a transitory signal per se, the program instruction executable by a processor to cause the processor to perform a method comprising:

determining a predicted object attribute for a target object by analyzing a prediction model;

capturing, by a camera, a first image and a second image, the second image being captured subsequent to the first image being captured, wherein the first and second images contain the target object;

determining a measured object attribute for the target object by comparing the first and second images;

determining whether the prediction model is correct by comparing the measured object attribute to the predicted object attribute; and

validating, in response to determining that the prediction model is correct, the prediction model.

14. The computer program product of claim 13, wherein the target object is a cloud, the object attribute is an angular velocity, and the prediction model is a weather forecast.

15. The computer program product of claim 14, wherein the determining a predicted object attribute comprises:

determining, from the weather forecast, a predicted cloud height;

determining, from the weather forecast, a predicted wind velocity at the predicted cloud height; and

calculating a predicted angular velocity for the cloud using the predicted wind velocity and the predicted cloud height.

16. The computer program product of claim 13, the method performed by the processor further comprising:

updating, in response to determining that the prediction model is incorrect, the prediction model using the measured object attribute.

17. The computer program product of claim 13, wherein the determining a measured object attribute for the target object comprises:

determining a first pixel location for the target object, the first pixel location corresponding to the first image;

determining a second pixel location for the target object, the second pixel location corresponding to the second image;

determining an image velocity by comparing the first pixel location and the second pixel location; and

determining the measured object attribute by applying an image transform to the image velocity.

18. The computer program product of claim 13, the method performed by the processor further comprising calibrating the camera by:

capturing a third image, the third image containing two or more celestial bodies;

determining a pixel location for each of the two or more celestial bodies;

determining a known location for the two or more celestial bodies; and

calibrating the camera by comparing the pixel locations for the two or more celestial bodies to the known location for the two or more celestial bodies.