Data Mining Method and System For Estimating Relative 3D Velocity and Acceleration Projection Functions Based on 2D Motions

• US 20110205355A1
• Filed: 02/19/2010
• Published: 08/25/2011
• Est. Priority Date: 02/19/2010
• Status: Abandoned Application

• Current Assignee: Panasonic Corporation (Panasonic Holdings Corporation)
• Original Assignee: Panasonic Corporation (Panasonic Holdings Corporation)
• Inventors: Lee, Kuo Chu, LIU, Lipin
• Application Number:
  US12/709,046
• Publication Number:
  US 20110205355A1
• Time in Patent Office: Days
• US Class Current: 348/135
• CPC Class Codes: G06T 2207/10016 Video; Image sequence
• CPC Class Codes: G06T 2207/30232 Surveillance
• CPC Class Codes: G06T 7/80 Analysis of captured images to determine intrinsic or extrinsic camera parameters, i.e. camera calibration

Abstract

A method for determining a transformation matrix used to transform data from a first image of a space to a second image of the space is disclosed. The method comprises receiving image data from a video camera monitoring the space, wherein the video camera generates image data of an object moving through the space and determining spatio-temporal locations of the object with respect to a field of view of the camera from the image data. The method further comprises determining observed attributes of motion of the object in relation to the field of view of the camera based on the spatio-temporal locations of the object, the observed attributes including at least one of a velocity of the object with respect to the field of view of the camera and an acceleration of the object with respect to the field of view of the camera. The method also includes determining the transformation matrix based on the observed attributes of the motion of the object.

Claims

1. A method for transforming data from a first image of a space to a second image of the space, the method comprising:

receiving image data from a video camera monitoring the space, wherein the video camera generates image data of an object moving through the space;

determining spatio-temporal locations of the object with respect to a field of view of the camera from the image data;

determining observed attributes of motion of the object in relation to the field of view of the camera based on the spatio-temporal locations of the object, the observed attributes including at least one of a velocity of the object with respect to the field of view of the camera and an acceleration of the object with respect to the field of view of the camera; and

determining the transformation matrix based on the observed attributes of the motion of the object.

2. The method of claim 1 further comprising transforming the first image of the space into the second image of the space.

3. The method of claim 2 further comprising calibrating the transformation matrix by

inserting a computer generated object into the first image;

transforming the computer generated object into a transformed object in the second image;

comparing the computer generated object and the transformed object; and

adjusting elements in the transformation matrix based on said comparing.

4. The method of claim 1 wherein said determining the transformation matrix is further based on actual attributes of motion with respect to the space, wherein the actual attributes of motion include a constant velocity with respect to the space of at least one of the object and another object.

5. The method of claim 1 wherein the field of view of the camera is divided into a plurality of cells.

6. The method of claim 5 wherein the spatio-temporal locations of the object are defined with respect to the plurality of cells.

7. The method of claim 6 further comprising generating a velocity map indicating a dominant flow direction of each cell of the plurality of cells and a cell velocity indicative of velocities of a plurality of observed objects in the cell moving in the dominant flow direction, wherein the cell velocity is defined with respect to the field of view of the camera and wherein the plurality of observed objects includes the object.

8. The method of claim 7 wherein said determining of the transformation matrix is based on the velocity map.

9. The method of claim 8 wherein said determining of the transformation matrix is further based on actual attributes of motion with respect to the space, wherein the actual attributes of motion include a constant velocity with respect to the space of at least one of the object and another object.

10. The method of claim 6 further comprising generating an acceleration map indicating a dominant flow direction of each cell of the plurality of cells and a cell acceleration indicative of accelerations of a plurality of observed objects in the cell moving in the dominant flow direction, wherein the cell acceleration is defined with respect to the field of view of the camera and wherein the plurality of observed objects includes the object.

11. The method of claim 10 wherein said determining of the transformation matrix is based on the acceleration map.

12. The method of claim 8 wherein said determining of the transformation matrix is further based on actual attributes of motion with respect to the space, wherein the actual attributes of motion include an acceleration having a value of zero, wherein the acceleration is with respect to the space and corresponds to at least one of the object and another object.

13. The method of claim 3 wherein said calibrating is performed iteratively.

14. A system for transforming data from a first image of a space to a second image of the space, the system comprising:

a metadata processing module configured to receive image data from a video camera monitoring the space, wherein the video camera generates image data of an object moving through the space and to determine spatio-temporal locations of the object with respect to a field of view of the camera from the image data;

a processing module configured to determine observed attributes of motion of the object in relation to the field of view of the camera based on the spatio-temporal locations of the object, the observed attributes including at least one of a velocity of the object with respect to the field of view of the camera and an acceleration of the object with respect to the field of view of the camera; and

a transformation module configured to determine the transformation matrix based on the observed attributes of the motion of the object.

15. The system of claim 14 wherein the transformation module is further configured to transform the first image of the space into the second image of the space.

16. The system of claim 15 further comprising a calibration module configured to

insert a computer generated object into the first image;

transform the computer generated object into a transformed object in the second image;

compare the computer generated object and the transformed object; and

adjusting elements in the transformation matrix based on said comparison.

17. The system of claim 14 wherein the transformation matrix is further based on actual attributes of motion with respect to the space, wherein the actual attributes of motion include a constant velocity with respect to the space of at least one of the object and another object.

18. The system of claim 14 wherein the field of view of the camera is divided into a plurality of cells.

19. The system of claim 18 wherein the spatio-temporal locations of the object are defined with respect to the plurality of cells.

20. The system of claim 19 further comprising a data fusion module configured to generate a velocity map indicating a dominant flow direction of each cell of the plurality of cells and a cell velocity indicative of velocities of a plurality of observed objects in the cell moving in the dominant flow direction, wherein the cell velocity is defined with respect to the field of view of the camera and wherein the plurality of observed objects includes the object.

21. The system of claim 20 wherein said the transformation matrix is based on the velocity map.

22. The system of claim 21 wherein said the transformation matrix is further based on actual attributes of motion with respect to the space, wherein the actual attributes of motion include a constant velocity with respect to the space of at least one of the object and another object.

23. The system of claim 19 further comprising a data fusion module that generates an acceleration map indicating a dominant flow direction of each cell of the plurality of cells and a cell acceleration indicative of accelerations of a plurality of observed objects in the cell moving in the dominant flow direction, wherein the cell acceleration is defined with respect to the field of view of the camera and wherein the plurality of observed objects includes the object.

24. The system of claim 23 wherein said the transformation matrix is based on the acceleration map.

25. The system of claim 24 wherein said the transformation matrix is further based on actual attributes of motion with respect to the space, wherein the actual attributes of motion include an acceleration having a value of zero, wherein the acceleration is with respect to the space and corresponds to at least one of the object and another object.