We’ve been working on a stereoscopic production, and we’ve been coming up with helpful tricks to make things just a tiny bit easier.  Here’s an example comp that shows a couple of them.

Position Pass and Camera Metadata Screengrab

Read the rest of this entry »

A sizable segment of the population suffers from color blindness, enough so that it’s worth considering the implications on color palettes and usability.  This tool allows you to simulate the ways that various color vision deficiencies will affect you imagery.  I’ve noticed that some of the images we create probably won’t read very well to some people, and this easily lets us check if we’ve created something that could be ambiguous.

ColorBlind fuse

Read the rest of this entry »

Fusion 6 added a Color Matrix tool that lets you enter your own matrix by hand, but the biggest problem with it is the lack of any methods to modify it with.  You can’t even assign controllers to it.

Fuses, however,  let you use handy methods to modify a matrix.  I’ve used some of them to create an RGB equivalent of the 3D Transform tool.  It has a similar UI, just as 3TT does, but this modifies RGB, not XYZ or UVW.

Color Matrix Transform fuse

Read the rest of this entry »

We’ve seen some pretty cool things at SIGGraph so far…

Gel Sight

Gel Sight is a retrographic surface imaging technique that was wonderfully elegant in it’s simplicity and effectiveness.  They also gave out free samples…

Cuda raycasting 13GB of cryomacrotome goodness (in stereo)

Nvidia had a stereographic interactive realtime rendering of the full 13GB Visible Human dataset being rendered in CUDA on 3 Quadroplexi.  Very impressive.  The glasses used were the new Nvidia active shutter glasses, and were very effective.

Resistive multitouch in many form factors

A new startup out of NYU showed a novel resistive multitouch device.  Very effective, low cost, and suitable to many applications.

UPDATE: Sorry about the broken link, Touchco was bought up by Amazon, so pretty much all of the cool applications they had in mind are replaced by the Kindle 3.

VLC madness courtesy 2 Fusion-io cards

Fusion-io showed their new “budget” nonvolatile storage adapter, the ioXtreme.   $900 gets you 80GB, with a read speed o 700MB/s.  The IO’s aren’t very high, much less their enterprise solutions, but that doesn’t matter if you are reading sequential data.  The booth was pretty crazy, too, one of the better live hardware demos I’ve seen in a while.  I’ll get some pictures tomorrow.  VLC never looked so impressive…

You never know what files you are going to get from customers.  After several phone calls talking through using FTP or shipping a hard drive, confirming compression usage, acceptable file formats there is still the possibility weird naming schemes.

This is example of a schema that came through last week.

I was about to whip out my favorite file renaming software, but I wanted to retain the original names for communication with the customer.  The solution is pretty easy so I thought I’d share it.  There might be a tool that does this already but its good to know how to do this on any machine without any special tool installed.  We’re going to fix this problem with CMD.exe. muahahaha!

Read the rest of this entry »

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.

In part one, I talked about the terrible technique used to fake the look of an x-ray image.  Now that I’ve snatched away an item from your bag-of-tricks, it’s only fair to replace it with a new technique. But before I do that. Let’s explore how x-ray imaging works.

Simple Definition

This is the standard illumination model, or how our eyes and cameras work. This is actually a tiny sub-set but you get the idea. Light sources emit energy that bounces off objects into a camera and absorbed by a sensor. This could be film or a CCD on a digital camera.  Actually the purpose of the camera isn’t so much collecting the light from the image, rather the camera is blocking the light that is not the image from exposing the film.  Light is coming from all directions and bouncing all over (not shown), but only the light that converges through the lens is captured.  This is not the case for x-rays. The whole point of x-ray imaging is to have the energy mostly penetrate the object and measure the how much reaches the sensor. This type of imaging is analogous to cast shadows.

Read the rest of this entry »

Trying out some new datasets and new techniques…

EDIT:  Jim asked for some more details, and I already had some images that I intended to post, but forgot about.  So here’s a breakdown of the three layers used to make the above image…

Chameleon rendered layers

The left layer is an environment map lookup, the middle is a front lit with high opacity, and the right is a backlit with low opacity.   These were then additively composited together.

I also did some tests on this dataset with clipping.

Chameleon culled with spherical gizmo

Chameleon culled with box

The box culling was an accident, but I thought it looked like a cut of meat that had been chewed on by mice.

Because we’re often trying to simulate small wet transparent things we rely pretty heavily on stochastic raytracing. We can handle transparency, large light sources, depth of field, light scattering, etc. all at the same time. It’s a general purpose setup that works well for a broad range of “soft” phenomenon. Brazil is pretty fast, but there are limits to our patience, especially since the sampling isn’t reusable. Once you make any change at all to the scene, you essentially have to start over. So we try to get a lot of revisions done to refine a look and still keep the speeds good so we can get those revisions turned around quickly.

When you reduce the number of samples, you get a large increase in speed, but the downside is aliasing, which generally looks like noise, since it is stochastic.

Read the rest of this entry »

So here’s my inaugural post…

SEM shaders, before and after

When I started working at Anatomical, we had a compositor (of sorts) working here who we would pass shots off to. Because a variety of reasons it wasn’t very effective, and so I pushed to have the process modified so that the people doing the 3D rendering were actively involved in the compositing workflow, and vice versa. Fast forward some years, and at this point, I comp nearly all of my own shots, and our “compositor” is pretty darn good with rendering from 3ds max.

Read the rest of this entry »