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In the above example, the workflow on the right takes the left and right eye, generates the disparity,
and then NewEye is used to generate a new eye for the image right away.
The example on the left renders the frames with disparity to intermediate EXR images. These images
are then loaded back into Stereo nodes and used to create the NewEye images.
By using Render nodes to compute the disparity first, the later processing of the creative operations
can be a much faster and interactive experience.
Although not shown in the above diagram, it is usually a good idea to color correct the right eye to be
similar to the left eye before disparity generation, as this helps with the disparity-tracking algorithm.
The color matching does not need to be perfect—for example, it can be accomplished using the
“Match” option in a Color Corrector’s histogram options.
About the Disparity Channel
The Disparity channel stores the displacement vectors that match pixels in one eye to the other eye.
The left image’s Disparity channel will contain vectors that map left>right and the right image’s
Disparity channel will contain vectors that map right>left. For example:
(xleft, yleft) + (Dleft. x, Dleft. y) -> (xright, yright) (xright, yright) +
(Dright. x, Dright. y) -> (xleft, yleft)
You would expect for non-occluded pixels that Dleft = -Dright, although, due to the disparity
generation algorithm, this is only an approximate equality.
NOTE: Disparity stores both X and Y values because rarely are left/right images perfectly
registered in Y, even when taken through a carefully set up camera rig.
Both Disparity and Optical Flow values are stored as un-normalized pixel shifts. In particular, note that
this breaks from Fusion’s resolution-independent convention. After much consideration, this
convention was chosen so the user wouldn’t have to worry about rescaling the Disparity/Flow values
when cropping an image or working out scale factors when importing/exporting these channels to
other applications. Because the Flow and Disparity channels store things in pixel shifts, this can cause
problems with Proxy and AutoProxy. Fusion follows the convention that, for proxied images, these
channels store unscaled pixel shifts valid for the full-sized image. So if you wish to access the Disparity
values in a script or via a probe, you need to remember to always scale them by (image. Width/image.
OriginalWidth, image. Height/ image. OriginalHeight).
Viewing of Disparity and Vector Channels
Aux channels can be displayed directly in the viewers through the Channel viewer button’s menu.
The CopyAux node is used to copy those channels directly into the RGB channels for viewing or
further processing. The advantage of using the CopyAux node is that it does static normalization,
which reduces a lot of flicker that the viewer’s time-variant normalization causes. When viewing long
sequences of aux channels, the CopyAux node has the option to kill off aux channels and keep only
the current RGB channels, freeing up valuable memory so you can cache more frames.
TIP: Although you can use the Channel Booleans to copy any aux channel into RGBA, it
involves a few additional clicks when compared to CopyAux.
Chapter 88Optical Flow and Stereoscopic Nodes 1597
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