Method and system for the dynamic calibration of stereovision cameras

1. A method of analyzing the stereovision image of a natural scene in order to produce an X/Y disparity map of the scene for use in the control of an adaptive or active system, the method comprising the steps of:

capturing first image data of the scene with a first sensor;

capturing second image data of the scene with a second sensor;

applying pyramidal decomposition to the first image data and second image data to produce a plurality of decomposition levels with each level having a set of image pairs derived from the first image data and second image data and wherein the image resolution at each subsequent decomposition level is lower than the image resolution at the preceding decomposition level;

executing a stereo disparity algorithm at each decomposition level; the algorithm assigning a predetermined disparity shift value to each decomposition level;

determining a disparity map at each decomposition level;

combining the disparity maps from all decomposition levels to form an initial X/Y disparity map of the scene where the disparity shift values compensate for resolution differences that exist between the decomposition levels;

estimating the pitch, roll, and yaw errors associated with angular misalignment of the first and second sensors on the captured image data;

correcting the image data for the pitch, roll, and yaw errors; and

determining a final X/Y disparity map;

wherein the stereo dispersity algorithm applies interpolation onto the image data instead of onto derived disparity data;

wherein the pitch, roll, and yaw errors are dynamically determined each time image data is captured.

2. The method according to claim 1 , wherein the first and second image data are represented by a continuous function equal to the summation of a gradient G(x,y) for the first image and gradient F(x,y) for the second image over the entire decomposition level.

3. The method according to claim 2 , wherein the gradient for the first and second images include factors describing the pixel location, disparity shift, X/Y disparity, and bias intensity at each decomposition level.

4. The method according to claim 1 , wherein pyramidal decomposition is accomplished using one selected from the group of pixel resize, pixel average, Gaussian, and a wavelet decomposition processing.

5. The method according to claim 1 , wherein the disparity map determined for a decomposition level is used as the initial disparity shift value for the next lower decomposition level.

6. The method according to claim 1 , wherein the X/Y disparity map is determined without pre-warping or finding the epipolar directions.

7. A stereovision system for producing an X/Y disparity map of a natural scene that can be used to control an adaptive or active system, the stereovision system comprising:

a first sensor adapted to capture a first image data of the scene;

a second sensor adapted to capture a second image data of the scene;

a processor being in communication with the first sensor and the second sensor;

the processor being configured to apply pyramidal decomposition to the first image data and second image data to produce a plurality of decomposition levels with each level having a set of image pairs derived from the first image data and second image data and wherein the image resolution at each subsequent decomposition level is lower than the image resolution at the preceding decomposition level;

the processor being configured to execute a stereo disparity algorithm at each decomposition level; the algorithm assigning a predetermined disparity shift value to each decomposition level;

the processor being configured to determine a disparity map at each decomposition level;

the processor being configured to combine the disparity maps from all decomposition levels to form an initial X/Y disparity map of the scene where the disparity shift values compensate for resolution differences that exist between the decomposition levels;

the processor being configured to estimate the pitch, roll, and yaw errors associated with angular misalignment of the first and second sensors on the captured image data;

the processor being configured to correct the image data for the pitch, roll, and yaw errors; and

the processor being configured to determine a final X/Y disparity map;

wherein the stereo dispersity algorithm applies interpolation onto the image data instead of onto derived disparity data;

wherein the pitch, roll, and yaw errors are dynamically determined each time image data is captured.

8. The method according to claim 7 , wherein the first and second image data are represented by a continuous function equal to the summation of a gradient G(x,y) for the first image and gradient F(x,y) for the second image over the entire decomposition level.

9. The system according to claim 8 , wherein the gradient for the first and second images include factors describing the pixel location, disparity shift, X/Y disparity, and bias intensity at each decomposition level.

10. The system according to claim 7 , wherein the processor is configured to determine the pyramidal decomposition using one selected from the group of pixel resize, pixel average, Gaussian, and a wavelet decomposition processing.

11. The system according to claim 7 , wherein the processor is configured to determine the disparity map for a decomposition level using the initial disparity shift value for the next lower decomposition level.

12. The system according to claim 7 , wherein the processor is configured to determine the X/Y disparity map without pre-warping or finding the epipolar directions.