I was working on a little job today with a 2D temporally variant scalar field.

You know, B&W footage.

I needed to find the parts of the data that were changing the most and compare them to the overall data and the maximum delta.

What I ended up with, once Ben pointed it out to me, was a simple example of calculus laid out in a couple tools.   The simplest case is just taking the frames I have and interpolating the same number of frames, so there’s no missing samples.  It’s silly, really.

But you can try it with other sampling, so there’s also an example of a Sobel filter, with a 1D kernel perpendicular to the normal 2D one.  Cute really.

If you checked out my interactive smoothing comp, you can see how I used a Sobel filter to make the forward facing laser pointer by looking at the differentiation of the R and G channels over time.  Same idea, just different way of expressing the temporal dimension.

I’m tossing in a Laplacian filter too, just for fun, it’s not useful for the calculus part, but it was easy to do, and shows how you can change the kernel to make different effects.  It’s possible to also evaluate 2D or 3D kernels this way, too.  The temporal offsets can be combined with spatial offsets so you could make a 3D blur filter, or a 3D sharpen.  Or a 3D Unsharp Mask, as I’ve also included.

We were recently commissioned to do some visualizations for a virtual colonoscopy procedure.   Also known as a colonography.   If you’re unfamiliar with the process, Wikipedia has enough information to give you a general overview. While there is a lot of information on the internet about the scanning process itself and what the patient will experience, there isn’t much about the ways in which the CT data can be analyzed once it is acquired.  So here’s a brief overview of what we at Anatomical Travelogue did with it.

Screengrab from the realtime colonoscopy demo

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We were recently commissioned to do some visualizations for a virtual colonoscopy procedure.   Also known as a colonography.   If you’re unfamiliar with the process, Wikipedia has enough information to give you a general overview. While there is a lot of information on the internet about the scanning process itself and what the patient will experience, there isn’t much about the ways in which the CT data can be analyzed once it is acquired.  So here’s a brief overview of what we at Anatomical Travelogue did with it.

Screengrab from the realtime colonoscopy demo

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Ok, so this one uses a free plugin, but if you REALLY wanted, you could make it with just Fusion tools.  Exercise left to the reader though, especially those poor Rotation users.

Unlike the previous example, this one does NOT bake out all the animation to one image, but instead uses an animated image to represent the data over time.  This makes it interactive and allows it to work with motion blur.

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Another in what is turning into a series of posts where standard Fusion tools are transformed into something very interesting…

I’m smoothing animation data (or adding noise or offsets or whatever) using nothing more than some Probes.

In this video, the green dots represent the original animation, the blue dots the smoothed animation, and the orange is the original with some noise added.