Walt Disney Animation Studios’ newest film, Zootopia, will be releasing in the United States three weeks from today. I’ve been working at Walt Disney Animation Studios on the the core development team for Disney’s Hyperion Renderer since July of last year, and the release of Zootopia is really special for me; Zootopia is the first feature film I’ve worked on. My actual role on Zootopia was fairly limited; so far, I’ve been spending most of my time and effort on the version of Hyperion for our next film, Moana (coming out November of this year). On Zootopia I basically only did support and bugfixes for Zootopia’s version of Hyperion (and I actually don’t even have a credit in Zootopia, since I hadn’t been at the studio for very long when the credits were compiled). Nonetheless, I’m incredibly proud of all of the work and effort that has been put into Zootopia, and I consider myself very fortunate to have been able to play even a small role in making the film!

Zootopia is a striking film in every way. The story is fantastic and original and relevant, the characters are all incredibly appealing, the setting is fascinating and immensely clever, the music is wonderful. However, on this blog, we are more interested in the technical side of things; luckily, the film is just as unbelievable in its technology. Quite simply, Zootopia is a breathtakingly beautiful film. In the same way that Big Hero 6 was several orders of magnitude more complex and technically advanced than Frozen in every way, Zootopia represents yet another enormous leap over Big Hero 6 (which can be hard to believe, considering how gorgeous Big Hero 6 is).

The technical advances made on Zootopia are far beyond what I can go into detail here since I don’t think I can describe them in a way that does them justice, but I think I can safely say that Zootopia is the most technically advanced animated film ever made to date. The fur and cloth (and cloth on top of fur!) systems on Zootopia are beyond anything I’ve ever seen, the sets and environments are simply ludicrous in both detail and scale, and of course the shading and lighting and rendering are jaw-dropping. In a lot of ways, many of the technical challenges that had to be solved on Zootopia can be summarized in a single word: complexity. Enormous care had to be put into creating believable fur and integrating different furry characters into different environments [Burkhard et al. 2016], and the huge quantities of fur in the movie required developing new level-of-detail approaches [Palmer and Litaker 2016] to make the fur manageable on both the authoring and rendering sides. The sheer number of crowds characters in the film also required developing a new crowds workflow [El-Ali et al. 2016], again to make both authoring and rendering tractable, and the complex jungle environments seen throughout most of the film similarly required new approaches to procedural vegetation [Keim et al. 2016]. Complexity wasn’t just a problem on a large scale though; Zootopia is also incredible rich in the smaller details. Zootopia was the first movie that Disney Animation deployed a flesh simulation system on [Milne et al. 2016] in order to create convincing muscular movement under the skin and fur of the animal characters. Even individual effects such as scooping ice cream [Byun et al. 2016] sometimes required innovative new CG techniques. On the rendering side the Hyperion team developed a brand new BSDF for shading hair and fur [Chiang et al. 2016], with a specific focus on balencing artistic controllability, physical plausibility, and render efficiency. Disney isn’t paying me to write this on my personal blog, and I don’t write any of this to make myself look grand either. I played only a small role, and really the amazing quality of the film is a testament to the capabilities of the hundreds of artists that actually made the final frames. I’m deeply humbled to see what amazing things great artists can do with the tools that my team makes.

Okay, enough rambling. Here are some stills from the film, 100% rendered with Hyperion, of course. Go see the film; these images only scratch the surface in conveying how gorgeous the film is.

All images in this post are courtesy of and the property of Walt Disney Animation Studios.

References

Nicholas Burkard, Hans Keim, Brian Leach, Sean Palmer, Ernest J. Petti, and Michelle Robinson. 2016. From Armadillo to Zebra: Creating the Diverse Characters and World of Zootopia. In ACM SIGGRAPH 2016 Production Sessions. Aritcle 24.

Dong Joo Byun, James Mansfield, and Cesar Velazquez. 2016. Delicious Looking Ice Cream Effects with Non-Simulation Approaches. In ACM SIGGRAPH 2016 Talks. Article 25.

Matt Jen-Yuan Chiang, Benedikt Bitterli, Chuck Tappan, and Brent Burley. 2016. A Practical and Controllable Hair and Fur Model for Production Path Tracing. Computer Graphics Forum (Proc. of Eurographics) 35, 2 (May 2016), 275-283.

Moe El-Ali, Joyce Le Tong, Josh Richards, Tuan Nguyen, Alberto Luceño Ros, and Norman Moses Joseph. 2016. Zootopia Crowd Pipeline. In ACM SIGGRAPH 2016 Talks. Article 59.

Hans Keim, Maryann Simmons, Daniel Teece, and Jared Reisweber. 2016. Art-Directable Procedural Vegetation in Disney’s Zootopia. In ACM SIGGRAPH 2016 Talks. Article 18.

Andy Milne, Mark McLaughlin, Rasmus Tamstorf, Alexey Stomakhin, Nicholas Burkard, Mitch Counsell, Jesus Canal, David Komorowski, and Evan Goldberg. 2016. Flesh, Flab, and Fascia Simulation on Zootopia. In ACM SIGGRAPH 2016 Talks. Article 34.

Sean Palmer and Kendall Litaker. 2016. Artist Friendly Level-of-Detail in a Fur-Filled World. In ACM SIGGRAPH 2016 Talks. Article 32.

A few months ago I added attenuation to Takua a0.5’s Fresnel refraction BSDF. Adding attenuation wound up being more complex than originally anticipated because handling attenuation through refractive/transmissive mediums requires volumetric information in addition to the simple surface differential geometry. In a previous post about my BSDF system, I mentioned that the BSDF system only considered surface differential geometry information; adding attenuation meant extending my BSDF system to also consider volume properties and track more information about previous ray hits.

First off, what is attenuation? Within the context of rendering and light transport, attenuation is when light is progressively absorbed within a medium, which results in a decrease in light intensity as one goes further and further into a medium away from a light source. One simple example is in deep water- near the surface, most of the light that has entered the water remains unabsorbed, and so the light intensity is fairly high and the water is fairly clear. Going deeper and deeper into the water though, more and more light is absorbed and the water becomes darker and darker. Clear objects gain color when light is attenuated at different rates according to different wavelengths. Combined with scattering, attenuation is a major contributing property to the look of transmissive/refractive materials in real life.

Attenuation is described using the Beer-Lambert Law. The part of the Beer-Lambert Law we are concerned with is the definition of transmittance:

The above equation states that the transmittance of a material is equal to the transmitted radiant flux over the received radiant flux, which in turn is equal to e raised to the power of the negative of the optical depth. If we assume uniform attenuation within a medium, the Beer-Lambert law can be expressed in terms of an attenuation coefficient μ as:

From these expressions, we can see that light is absorbed exponentially as distance into an absorbing medium increases. Returning back to building a BSDF system, supporting attenuation therefore means having to know not just the current intersection point and differential geometry, but also the distance a ray has traveled since the previous intersection point. Also, if the medium’s attenuation rate is not constant, then an attenuating BSDF not only needs to know the distance since the previous intersection point, but also has to sample along the incoming ray at some stepping increment and calculate the attenuation at each step. In other words, supporting attenuation required BSDFs to know the previous hit point in addition to the current one and also requires BSDFs to be able to ray march from the previous hit point to the current one.

Adding previous hit information and ray march support to my BSDF system was a very straightforward task. I also added volumetric data support to Takua, allowing for the following attenuation test with a glass Stanford Dragon filled with a checkerboard red and blue medium. The red and blue medium is ray marched through to calculate the total attenuation. Note how the thinner parts of the dragon allow more light through resulting in a lighter appearance, while thicker parts of the dragon attenuate more light resulting in a darker appearance. Also note the interesting red and blue caustics below the dragon:

Things got much more complicated once I added support for what I call “deep attenuation”- that is, attenuation through multiple mediums embedded inside of each other. A simple example is an ice cube floating in a glass of liquid, which one might model in the following way:

There are two things in the above diagram that make deep attenuation difficult to implement. First, note that the ice cube is modeled without a corresponding void in the liquid- that is, a ray path that travels through the ice cube records a sequence of intersection events that goes something like “enter water, enter ice cube, exit ice cube, exit water”, as opposed to “enter water, exit water, enter ice cube, exit ice cube, enter water, exit water”. Second, note that the liquid boundary is actually slightly inside of the inner wall of the glass. Intuitively, this may seem like a mistake or an odd property, but this is actually the correct way to model a liquid-glass interface in computer graphics- see this article and this other article for details on why.

So why do these two cases complicate things? As a ray enters each new medium, we need to know what medium the ray is in so that we can execute the appropriate BSDF and get the correct attenuation for that medium. We can only evaluate the attenuation once the ray exits the medium, since attenuation is dependent on how far through the medium the ray traveled. The easy solution is to simply remember what the BSDF is when a ray enters a medium, and then use the remembered BSDF to evaluate attenuation upon the next intersection. For example, imagine the following sequence of intersections:

1. Intersect glass upon entering glass.
2. Intersect glass upon exiting glass.
3. Intersect water upon entering water.
4. Intersect water upon exiting water.

This sequence of intersections is easy to evaluate. The evaluation would go something like:

1. Enter glass. Store glass BSDF.
2. Exit glass. Evaluate attenuation from stored glass BSDF.
3. Enter water. Store water BSDF.
4. Exit water. Evaluate attenuation from stored water BSDF.

So far so good. However, remember that in the first case, sometimes we might not have a surface intersection to mark that we’ve exited one medium before entering another. The following scenario demonstrates how this first case results in missed attenuation evaluations:

1. Intersect water upon entering water.
2. Exit water, but no intersection!
3. Intersect ice upon entering ice.
4. Intersect ice upon exiting ice.
5. Enter water again, but no intersection either!
6. Intersect water upon exiting water.

The evaluation sequence ends up playing out okay:

1. Enter water. Store water BSDF.
2. Exit water, but no intersection. No BSDF evaluated.
3. Enter ice. Intersection occurs, so evaluate attenuation from stored water BSDF. Store ice BSDF.
4. Exit ice. Evaluate attenuation from stored ice BSDF.
5. Enter water again, but no intersection, so no BSDF stored.
6. Exit water…. but there is no previous BSDF stored! No attenuation is evaluated!

Alternatively, in step 6, instead of no previous BSDF, we might still have the ice BSDF stored and evaluate attenuation based on the ice. However, this result is still wrong, since we’re now using the ice BSDF for the water.

One simple solution to this problem is to keep a stack of previously seen BSDFs with each ray instead of just storing the previously seen BSDF. When the ray enters a medium through an intersection, we push a BSDF onto the stack. When the ray exits a medium through an intersection, we evaluate whatever BSDF is on the top of the stack and pop the stack. Keeping a stack works well for the previous example case:

1. Enter water. Push water BSDF on stack.
2. Exit water, but no intersection. No BSDF evaluated.
3. Enter ice. Intersection occurs, so evaluate water BSDF from top of stack. Push ice BSDF on stack.
4. Exit ice. Evaluate ice BSDF from top of stack. Pop ice BSDF off stack.
5. Enter water again, but no intersection, so no BSDF stored.
6. Exit water. Intersection occurs, so evaluate water BSDF from top of stack. Pop ice BSDF off stack.

Excellent, we now have evaluated different medium attenuations in the correct order, haven’t missed any evaluations or used the wrong BSDF for a medium, and as we exit the water and ice our stack is now empty as it should be. The first case from above is now solved… what happens with the second case though? Imagine the following sequence of intersections where the liquid boundary is inside of the two glass boundaries:

1. Intersect glass upon entering glass.
2. Intersect water upon entering water.
3. Intersect glass upon exiting glass.
4. Intersect water upon exiting water.

The evaluation sequence using a stack is:

1. Enter glass. Push glass BSDF on stack.
2. Enter water. Evaluate glass attenuation from top of stack. Push water BSDF.
3. Exit glass. Evaluate water attenuation from top of stack, pop water BSDF.
4. Exit water. Evaluate glass attenuation from top of stack, pop glass BSDF.

The evaluation sequence is once again in the wrong order- we just used the glass attenuation when we were traveling through water at the end! Solving this second case requires a modification to our stack based scheme. Instead of popping the top of the stack every time we exit a medium, we should scan the stack from the top down and pop the first instance of a BSDF matching the BSDF of the surface we just exited through. This modified stack results in:

1. Enter glass. Push glass BSDF on stack.
2. Enter water. Evaluate glass attenuation from top of stack. Push water BSDF.
3. Exit glass. Evaluate water attenuation from top of stack. Scan stack and find first glass BSDF matching the current surface’s glass BSDF and pop that BSDF.
4. Exit water. Evaluate water attenuation from top of stack. Scan stack and pop first matching water BSDF.

At this point, I should mention that pushing/popping onto the stack should only occur when a ray travels through a surface. When the ray simply reflects off of a surface, an intersection has occurred and therefore attenuation from the top of the stack should still be evaluated, but the stack itself should not be modified. This way, we can support diffuse inter-reflections inside of an attenuating medium and get the correct diffuse inter-reflection with attenuation between diffuse bounces! Using this modified stack scheme for attenuation evaluation, we can now correctly handle all deep attenuation cases and embed as many attenuating mediums in each other as we could possibly want.

…or at least, I think so. I plan on running more tests before conclusively deciding this all works. So there may be a followup to this post later if I have more findings.

A while back, I wrote a PIC/FLIP fluid simulator. However, at the time, Takua Renderer didn’t have attenuation support, so I wound up rendering my simulations with Vray. Now that Takua a0.5 has robust deep attenuation support, I went back and used some frames from my fluid simulator as tests. The image at the top of this post is a simulation frame from my fluid simulator, rendered entirely with Takua a0.5. The water is set to attenuate red and green light more than blue light, resulting in the blue appearance of the water. In addition, the glass has a slight amount of hazy green attenuation too, much like real aquarium glass. As a result, the glass looks greenish from the ends of each glass plate, but is clear when looking through each plate, again much like real glass. Here are two more renders:

I realize I have not posted in some weeks now, which means I still haven’t gotten around to writing up Takua a0.5’s architecture and VCM integrator. I’m hoping to get to that once I’m finished with my thesis work. In the meantime, here are some more pretty pictures rendered using Takua a0.5.

A few months back, I made a high-complexity scene designed to test Takua a0.5’s capability for handling “real-world” workloads. The scene was also designed to have an extremely difficult illumination setup. The scene is an indoor room that is lit primarily from outside through glass windows. Yes, the windows are actually modeled as geometry with a glass BSDF! This means everything seen in these renders is being lit primarily through caustics! Of course, no real production scene would be set up in this manner, but I chose this difficult setup specifically to test the VCM integrator. There is a secondary source of light from a metal cylindrical lamp, but this light source is also difficult since the actual light is emitted from a sphere light inside of a reflective metal cylinder that blocks primary visibility from most angles.

The flowers and glass vase are the same ones from my earlier Flower Vase Renders post. The original flowers and vase are by Andrei Mikhalenko, with custom textures of my own. The amazing, colorful Takua poster on the back wall is by my good friend Alice Yang. The two main furniture pieces are by ODESD2, and the Braun SK4 record player model is by one of my favorite archviz artists, Bertrand Benoit. The teapot is, of course, the famous Utah teapot. All textures, shading, and other models are my own.

As usual, all depth of field is completely in-camera and in-renderer. Also, all BSDFs in this scene are fairly complex; there is not a single simple diffuse surface anywhere in the scene! Instancing is used very heavily; the wicker baskets, notebooks, textbooks, chess pieces, teacups, and tea dishes are all instanced from single pieces of geometry. The floorboards are individually modeled but not instanced, since they all vary in length and slightly in width.

A few more pretty renders, all rendered in Takua a0.5 using VCM:

Just a quick note on images on this blog. So far, I’ve generally been embedding full resolution, losslessly compressed PNG format images in the blog. I prefer having the full resolution, lossless images available on the blog since they are the exact output from my renderer. However, full resolution lossless PNGs can get fairly large (several MB for a single 1920x1080 frame), which is dragging down the load times for the blog.

Going forward, I’ll be embedding lossy compressed JPG images in blog posts, but the JPGs will link through to the full resolution, lossless PNG originals. Fortunately, high quality JPG compression is quite good these days at fitting an image with nearly imperceptible compression differences into a much smaller footprint. I’ll also be going back and applying this scheme to old posts too at some point.

Addendum 2016-04-08

Now that I am doing some renders in 4K resolution (3840x2160), it’s time for an addendum to this policy. I won’t be uploading full resolution lossless PNGs for 4K images, due to the overwhelming file size (>30MB for a single image, which means a post with just a handful of 4K images can easily add up to hundreds of MB). Instead, for 4K renders, I will embed a downsampled 1080P JPG image in the post, and link through to a 4K JPG compressed to balance image quality and file size.