How to use this page
- Fill in the appropriate data in all the form-fields of the previous page.
We already filled in an example that should work.
- After submitting your job, our server will try to fetch your images,
convert them into an internal floating-point image format, do some
preliminary checks and finally start the calculations.
- You will be shown a log-file of your request, where you can watch this
process. The results will simply be attached to the end of the log-file.
- If your browser can not handle automatic updates (most browsers can),
you have to push the RELOAD-button of your browser once in a while to get
the current status.
- After your calculations are finished, the results are stored at our
server for further reference. However, after one or two days, the data
will no longer be available to you.
The implemented algorithm
has a specific range over which the correlation-measure is maximized.
similar to human stereo vision.
You can select either:
- Automatic Vergence Control: a vergence system tries
to align the stereo images automatically. This might fail, in which
case you should try the "Fixed Disparity Range"-setting instead.
The entry total disparity range
sets the search region for the algorithm, which is restricted to maximal
20 pixels. In some cases you might get better results if you
disable Allow for rotation, which constrains the vergence
system to use only horizontal or vertical panning for alignment.
- Fixed Disparity Range: if you know that your images
have no vertical disparity component, and if you know the range
of horizontal disparities in advance, this is the setting for you.
You can choose between two basic correlation measures:
Try to compare the performance of both algorithms with the algorithms where
the mean image intensity is subtracted before disparity calculation.
These algorithms should perform better because of the normalization of image
- Sum-of-Squared Differences (SSD): as the name suggests, the
squared intensity differences between left and right image patch is summed.
The algorithm tries to minimize this value.
- Correlation: - basically the scalar product between the image
intensity of the left and right image patches, interpreted as vectors. The
algorithm tries to maximize this value.
Normally, the disparity map is only integer-valued. In order to obtain
disparity estimates with sub-pixel precision, two methods can be used:
- Subpixel-Interpolation - a simple, but effective method, except if the
image-data is composed of very high spatial frequencies. The minimum of the
correlation measure is calculated out of three neighbouring measurements by
fitting a low-order polynomial through the data.
- Iterative Refinement - an iterative
postprocessing algorithm is applied, which tries to refine the raw
When things go wrong
- Most problems occur in accessing your data by our server. We can
handle http-, ftp- and gopher-protocol. Be sure to
give a correct URL. You might
check the URL you supplied to our software by opening this location in your
own browser. But be sure to check by opening over the WEB, not
locally. If your browser can fetch your data, the URL should be fine. If our
server still can't fetch your data, please contact us.
- The algorithms have been designed to be fairly bullet-proof, but if you
do not enter correct values, you won't get any sensible results.
- This server is used also other purposes. If a certain load-average is
exceeded, this service is temporarily suspended.
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