UMBC researchers develop better techniques to
render video game characters with realistic skin

Researchers at the University of Maryland, Baltimore County (UMBC) have developed a new solution to render an essential detail in many video games: human skin. The research is published in the Proceedings of the Association for Computing Machinery on Computer Graphics and Interactive Techniques [1]. Marc Olano, associate professor of computer science and electrical engineering at UMBC, led this research alongside Tiantian Xie, Ph.D. ’22, computer science. Xie, under the guidance of Olano, has worked with researchers Brian Karis and Krzysztof Narkowicz at the gaming company Epic Games, developing a keen understanding of gamers’ user experience, including the precise level of realism and detail that players are looking for in human characters.

Game developers seek to create visuals that are as realistic as possible without stepping into the “uncanny valley.” This term describes when the graphics in a game attempt to portray a human as closely as possible, and gets close to mimicking real life, but not quite close enough, in a way users find disturbing. This creates an unpleasant feeling in users that might distract from their enjoyment of the game.

In many games, human skin is rendered in such a way that it looks like a plastic object. This plastic look can occur because animators aren’t accounting for subsurface scattering – a key element of how light interacts with a textured 3D surface. Subsurface scattering is animators’ main priority when it comes to transforming skin from looking like plastic to looking truly real.

Olano’s method builds upon research developed by large gaming companies to create realistic depictions of human skin that will also load quickly within a gaming interface. “Our method adds an ability to adaptively estimate how many samples you actually need to get the look that you want without having to do a lot of additional computation to get a smooth image,” explains Olano.

The method minimizes the amount of computation needed to create photo-realistic images. Previous techniques were either not realistic enough, or ran too slowly for use in games, negatively affecting the gaming experience. The new method is based on techniques developed for offline film production rendering. Xie, the first author of the paper, states, “Offline rendering techniques are not suitable for real-time rendering because adding the technique itself in real-time introduces a large overhead. Our technique eliminates this overhead.”

Olano and his team created an algorithm to determine the pixels that would need to be rendered differently than the others due to light gradient change. Their sampling method uses temporal variance to lower the overall number of changes within each frame while still maintaining a realistic depiction of subsurface scattering. Since fewer changes are needed per frame, the method creates an efficient way of rendering realistic skin within the capabilities of today’s computing power.

The algorithm used by Olano’s team is built upon a foundation of research that is known and accessible to game developers. This offers a promising path for the gaming industry to pursue realism while maintaining an awareness of the computational ability of an average gaming system. Developers may be able to begin using this technique soon to create more realistic human figures in games, growing the gaming market even more.

[1] Tiantian Xie, Marc Olano, Brian Karis, and Krzysztof Narkowicz. 2020. Real-time subsurface scattering with single pass variance-guided adaptive importance sampling. Proc. ACM Comput. Graph. Interact. Tech. 3, 1, Article 3 (Apr 2020), 21 pages. DOI:https://doi.org/10.1145/3384536

Adapted from a press release written by Morgan Zepp that appeared in EurikAlert.

The post UMBC researchers develop better techniques to render characters with realistic skin appeared first on Department of Computer Science and Electrical Engineering.

ByZoe McLaren, associate professor, public policy, UMBC

A commonly used malaria drug was recently proposed as a treatment for COVID-19 during a White House press briefing, even though it hadn’t yet been properly evaluated in clinical trials or approved for this use. Does the urgency of the current pandemic give doctors a good reason to skip evaluation and rush an untested drug to patients?

The field of medicine considers randomized-controlled trials, also known as “clinical trials,” as the gold standard for assessing the effectiveness of new treatments. These studies set up a fair test for treatments and enable researchers to rule out alternate explanations. Without randomized-controlled trial evidence to guide them, doctors risk wasting resources on ineffective treatments or causing harm to patients.

What is a randomized-controlled trial?

A controlled trial means that study participants are split into two groups: One group is given the treatment and the other (the control group) is not. The control group may be given a placebo that mimics the actual treatment, but does not contain the treatment being tested.

For example, a sugar pill or an injection of saline solution may be used instead of a dose of the drug. This ensures the only meaningful difference between the two groups is whether they received the treatment or not.

The control group helps researchers learn what would have happened to the treatment group if they hadn’t received the treatment. For example, some patients may recover on their own. Researchers need to know how often this happens, so they don’t attribute all recoveries to the effect of the treatment.

Study participants are randomly assigned to one group or the other, a process similar to a coin toss. Just as a coin toss is equally likely to end up heads or tails, study participants are equally likely to end up in the treatment or the control group. With enough study participants, this results in two groups that closely resemble each other. The only difference is that one group got “heads” while the other got “tails.”

The randomization of randomized-controlled trials with large enough samples ensures that all possible differences are accounted for, even those that may not be observed, such as genetic traits.

If the treatment and control groups are similar at the start of the study but end up with different outcomes, the treatment is the most likely cause. The randomized-controlled trial allows researchers to rule out alternative explanations.

What if patients aren’t randomly assigned?

If doctors were allowed to choose which patients received the treatment, it’s likely the treatment and control groups would not resemble each other, making it much harder to rule out different factors at play.

For example, malaria drugs aren’t approved for use against COVID-19, but may be prescribed to patients under the Food and Drug Administration’s “expanded access” program. It allows certain drugs to be used as a last resort to treat seriously ill patients when no other treatments are available.

These “last resort” patients are frailer than those who had a milder form of the disease or who responded well to other treatments. When you’re comparing very sick patients to healthier patients, the effect of the treatment is hard to see because it may be obscured by important differences such as age, diet, cigarette use, heart disease or obesity.

If frail patients on treatment fared significantly better than strong patients without it, researchers could conclude the treatment was effective. But this situation is extremely rare, which is why doctors generally can’t draw valid conclusions about a drug’s effectiveness in a “last resort” situation. Too many other factors are likely at play.

Some researchers may be able to use sophisticated statistics techniques to account for the differences between frail and strong patients. But there is a long list of potential differences between frail and strong patients, so it is hard to address them all. Gauging the quality of such statistical analysis is also difficult, so these studies should be viewed with skepticism.

Approving drugs prematurely

Without results from randomized-controlled trials, doctors can’t be sure whether a potential new treatment will help patients, harm them or prove ineffective.

The case of the malaria drug hydroxychloroquine as a potential treatment for COVID-19 underscores this concern. In an early wave of optimism, doctors prescribed and some even stockpiled so much hydroxychloroquine that pharmacies reported shortages of the drug. Within weeks however, randomized-controlled trials demonstrated that not only was this treatment ineffective against COVID-19, it also caused some patients to develop serious heart rhythm problems. Prematurely prescribing this treatment to all but the “last resort” cases instilled false hope, wasted medical resources and, most importantly, put patients at risk.

*****

Zoe McLaren, Associate Professor of Public Policy, University of Maryland, Baltimore County

[You need to understand the coronavirus pandemic, and we can help. Read The Conversation’s newsletter.]

This article is republished from The Conversation under a Creative Commons license. Read the original article.

Header image: Yulia Reznikov/Movement via Getty Images