Parameters
Disparity pre-filtering
- Normalization window size, pixels.
- Bound on normalized pixel values.
Disparity correlation
- Edge size (pixels) of the correlation window for matching. Values must be odd, in the range 5 to 255 (but with an extra performance hit for values larger than 21). Larger values have smoother disparity results, but smear out small features and depth discontinuities.
- Minimum disparity, or the offset to the disparity search window. By setting to a positive value, the cameras become more "cross-eyed" and will find objects closer to the cameras. If the cameras are "verged" (inclined toward each other), it may be appropriate to set min_disparity to a negative value. When min_disparity is greater than 0, objects at large distances will not be found.
- The size of the disparity search window (pixels). Together with min_disparity, this defines the "horopter," the 3D volume that is visible to the stereo algorithm.
Disparity post-filtering
- Filters disparity readings based on a comparison to the next-best correlation along the epipolar line. Matches where uniqueness_ratio > (best_match - next_match) / next_match are filtered out.
- Filters disparity readings based on the amount of texture in the correlation window.
- Filters disparity regions that are less than this number of pixels. For example, a value of 100 means that all regions with fewer than 100 pixels will be rejected.
- Groups disparity regions based on their connectedness. Disparities are grouped together in the same region if they are within this distance in pixels.
Synchronization
- Whether to use approximate synchronization. Set to true if the left and right cameras do not produce exactly synced timestamps.
- Size of message queue for each synchronized topic. You may need to raise this if images take significantly longer to travel over the network than camera info and/or the delay from disparity processing is too long.