Method and system for the dynamic calibration of stereovision cameras
First Claim
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.
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Abstract
The present invention generally provides a method of performing dynamic calibration of a stereo vision system using a specific stereo disparity algorithm adapted to provide for the determination of disparity in two dimensions, X and Y. In one embodiment of the present invention, an X/Y disparity map may be calculated using this algorithm without having to perform pre-warping or first finding the epipolar directions. Thus information related to camera misalignment and/or distortion can be preserved in the resulting X/Y disparity map and later extracted.
16 Citations
12 Claims
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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:
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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. - View Dependent Claims (2, 3, 4, 5, 6)
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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:
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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. - View Dependent Claims (8, 9, 10, 11, 12)
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Specification