Flight parameter measurement system

• US 20040032970A1
• Filed: 06/06/2003
• Published: 02/19/2004
• Est. Priority Date: 06/06/2002
• Status: Active Grant

• Current Assignee: Wawgd Newco LLC
• Original Assignee: Wintriss Engineering Corporation
• Inventors: Kiraly, Chris
• Granted Patent: US 7,324,663 B2
• Time in Patent Office: Days
• US Class Current: 382/103
• CPC Class Codes: A63B 2024/0031 at the starting point
• CPC Class Codes: A63B 2024/0037 on a target surface or at impact on the ground
• CPC Class Codes: A63B 2102/24 Ice hockey
• CPC Class Codes: A63B 2220/35 Spin
• CPC Class Codes: A63B 24/0021 Tracking a path or terminating locations
• CPC Class Codes: A63B 69/3658 Means associated with the ball for indicating or measuring, e.g. speed, direction
• CPC Class Codes: G01S 3/784 using a mosaic of detectors
• CPC Class Codes: G01S 3/7865 using correlation of the live video image with a stored image

Abstract

A portable flight parameter measurement system is a standalone smart camera which tracks the surface of an object in motion, e.g., a ball, and determines speed, trajectory, a spin axis, and a spin rate around that axis. The measurement system is particularly suited for analyzing the path of a ball in flight which is determined, in great part, by the amount of spin and the direction of spin imparted to the ball upon impact. The measurement system provides a user, such as a golfer, with important feedback for modifying his or her swing to obtain desired results. The measurement system utilizes non-precision marks, surface blemishes such as cuts made by a club, dimples, or a combination of all three as the only features necessary to determine ball flight characteristics.

Claims

1. A method for determining parameters of an object in motion, the method comprising the steps of:

calibrating a camera lens to establish (x, y, z) directions for every (x, y) pixel in an image plane of the camera;

determining alignment correction factors;

capturing a plurality of images of the object in motion;

finding the object in each of the plurality of images;

calculating three dimensional coordinates for each of the plurality of images;

calculating a velocity vector for the object from the three dimensional coordinates;

rotating a reference image of the plurality of images by a first set of rotations of a plurality of rotation sets;

scaling the rotated reference image to a target image;

correlating the reference image to the target image to obtain an incremental score of a plurality of scores;

repeating the steps of rotating, scaling and correlating in a stepwise refinement manner to obtain a best score of the plurality of scores; and

utilizing a best rotation set of the plurality of rotation sets to determine the parameters of the object in motion.

2. The method of claim 1, wherein the objects in motion are substantially spherical.

3. The method of claim 1, wherein the step of determining alignment correction factors further comprises the step of using an accelerometer to provide electrical signals to the camera for indicating misalignment of the camera relative to a surface.

4. The method of claim 1, step of calibrating a camera lens further comprises the steps of:

imaging a target at a near position;

recording the (x, y) coordinates for each pixel in the image plane at the near position;

imaging the target at a far position; and

recording the (x, y) coordinates for each pixel in the image plane at the far position.

5. The method of claim 1, wherein the step of capturing images of the object further comprises step of triggering the camera.

6. The method of claim 1, wherein the step of finding the object in each of the plurality of images further comprises the steps of:

finding the center of the object;

finding a diameter of the object; and

calculating a distance to the object.

7. The method of claim 1, further comprising the steps of:

determining an elevation angle and an azimuth angle of the object from the three dimensional coordinates for each of the plurality of images.

8. The method of claim 7, wherein the step of rotating the reference image of the plurality of images by the first set of rotations further comprises the step of rotating the reference image to a canonical view.

9. The method of claim 1, further comprising the step of removing glint from the plurality of images.

10. The method of claim 1, further comprising step of light-normalizing the plurality of images.

11. A measurement system for determine at least one characteristic of an object in motion, the measurement system comprising:

a camera lens for capturing a plurality images;

a memory means coupled to the camera lens for storing the plurality of images;

a triggering means for commencing image capture of the plurality of images; and

a processor coupled to the memory means, the processor comprising;

means for finding the object in motion in the plurality of images;

means for calculating three dimensional coordinates for each of the plurality of images;

mean for rotating a reference image of the plurality by a set of rotations of a plurality of rotation sets;

means for scaling the rotated reference image to a target image of the plurality of images;

means for correlating the rotated reference image to the target image to obtain a score; and

means for utilizing a best rotation set of the plurality of rotation sets to determine the at least one characteristic of the object in motion

12. The measurement system as in claim 11, further comprising means for calibrating the camera to determine x, y coordinates for each pixel in the camera field of view.

13. The measurement system as in claim 12, wherein the means for calibrating the camera comprises means for mapping an image of a target placed in a first position onto an image plane of the camera to obtain the (x,y) coordinates for each pixel in the image plane at the first position, and for mapping an image of the target placed in a second position onto the image plane to obtain the (x,y) coordinates for the each pixel in the image plane at the second position.

14. The measurement system as in claim 11, further comprising a structured light source that is spatially calibrated to intersect a field of view of the camera, wherein at least one of the plurality of images is illuminated by the structured light source.

15. The measurement system as in claim 11, further comprising a display for outputting the at least one characteristic of the object in motion.

16. The measurement system as in claim 11, further comprising at least one input/output port coupled to the processor for connecting at least one optional devices.

17. The measurement system as in claim 12, wherein the at least one optional device is a radio frequency transceiver for transmitting the at least one characteristic of the object in motion.

18. A method for determining a spin axis and rotation of a ball, the method comprising the steps of:

a. acquiring at least a reference ball image and a target ball image;

b. determining the real world coordinates of the reference ball image and the target ball image;

c. rotating the reference ball image by a first set of rotations to a canonical view utilizing the real world coordinates;

d. rotating the reference ball image by a second set of trial rotations;

e. rotating the reference ball image by a third set of rotation corresponding to a canonical view of the target ball image;

f. scaling the reference ball image to the target ball image;

g. correlating the reference ball image to the target ball image to obtain a score of a plurality of scores; and

h. repeating steps c through g in a stepwise refinement manner to obtain a best score of the plurality of scores.

19. The method of claim 18, further comprising the step of removing glint form the reference ball image and the target ball image.

20. The method of claim 18, further comprising the step of light-normalizing the plurality of images.