Jorge Jimenez

Screen-space perceptual rendering of human skin

We propose a novel skin shader which translates the simulation of subsurface scattering from texture space to a screen-space diffusion approximation. It naturally scales well while maintaining a perceptually plausible result. This technique allows us to ensure real-time performance even when several characters may appear on screen at the same time. The visual realism of the resulting images is validated using a subjective psychophysical preference experiment. Our results show that, independent of distance and light position, the images rendered using our novel shader have as high visual realism as a previously developed physically-based shader.

A practical appearance model for dynamic facial color

Facial appearance depends on both the physical and physiological state of the skin. As people move, talk, undergo stress, and change expression, skin appearance is in constant flux. One of the key indicators of these changes is the color of skin. Skin color is determined by scattering and absorption of light within the skin layers, caused mostly by concentrations of two chromophores, melanin and hemoglobin. In this paper we present a real-time dynamic appearance model of skin built from in vivo measurements of melanin and hemoglobin concentrations. We demonstrate an efficient implementation of our method, and show that it adds negligible overhead to existing animation and rendering pipelines. Additionally, we develop a realistic, intuitive, and automatic control for skin color, which we term a skin appearance rig. This rig can easily be coupled with a traditional geometric facial animation rig. We demonstrate our method by augmenting digital facial performance with realistic appearance changes.

Filtering approaches for real-time anti-aliasing

For more than a decade, supersample anti-aliasing (SSAA) and multisample anti-aliasing (MSAA) have been the gold-standard anti-aliasing solutions in games. However, these techniques are not well suited for deferred shading or fixed environments like the current generation of consoles. In recent years, industry and academia have been exploring alternative approaches, where anti-aliasing is performed as a post-processing step. The original, CPU-based morphological anti-aliasing (MLAA) method gave birth to an explosion of real-time anti-aliasing techniques that rival MSAA. Most of these techniques share concepts and ideas, so the main goal of this course is to establish a conceptual link between them, identifying novelties and differences. The presenters explain how sub-pixel data can be used to improve quality and performance tradeoffs at post-processing steps, which is a cutting-edge research area today. The course includes an overview of both research and industry filter-based anti-aliasing techniques in games for all modern platforms (AMD and NVIDIA GPUs, PlayStation 3, and Xbox 360), low-level insight to ease adoption of these techniques and give attendees a complete concept-to-implementation roadmap, and deep quality, performance, and ease-of-integration comparisons of each technique.

SMAA: Enhanced Subpixel Morphological Antialiasing

We present a new image‐based, post‐processing antialiasing technique, which offers practical solutions to the common, open problems of existing filter‐based real‐time antialiasing algorithms. Some of the new features include local contrast analysis for more reliable edge detection, and a simple and effective way to handle sharp geometric features and diagonal lines. This, along with our accelerated and accurate pattern classification allows for a better reconstruction of silhouettes. Our method shows for the first time how to combine morphological antialiasing (MLAA) with additional multi/supersampling strategies (MSAA, SSAA) for accurate subpixel features, and how to couple it with temporal reprojection; always preserving the sharpness of the image. All these solutions combine synergies making for a very robust technique, yielding results of better overall quality than previous approaches while more closely converging to MSAA/SSAA references but maintaining extremely fast execution times. Additionally, we propose different presets to better fit the available resources or particular needs of each scenario.

Real-Time Realistic Skin Translucency

A new algorithm renders real time, photorealistic skin by simulating both reflectance and transmittance of light through a multilayered skin model. Despite this models simplicity, it reproduces the look of images rendered with techniques such as photon mapping or diffusion approximation.

Stylized depiction of images based on depth perception

Recent works in image editing are opening up new possibilities to manipulate and enhance input images. Within this context, we leverage well-known characteristics of human perception along with a simple depth approximation algorithm to creatively relight images for the purpose of generating non-photorealistic renditions that would be difficult to achieve with existing methods. Our realtime implementation on graphics hardware allows the user to efficiently explore artistic possibilities for each image. We show results produced with four different styles proving the versatility of our approach, and validate our assumptions and simplifications by means of a user study.

A micro-grid battery storage management

An increase in number of distributed generation (DG) units in power system allows the possibility of setting-up and operating micro-grids. In addition to a number of technical advantages, micro-grid operation can also reduce running costs by optimally scheduling the generation and/or storage systems under its administration. This paper presents an optimized scheduling of a micro-grid battery storage system that takes into account the next-day forecasted load and generation profiles and spot electricity prices. Simulation results show that the battery system can be scheduled close to optimal even with forecast errors. ICLOCS software has been used for the numerical implementation.

Extended papers from NPAR 2010: Non-photorealistic, depth-based image editing

Recent works in image editing are opening up new possibilities to manipulate and enhance input images. Within this context, we leverage well-known characteristics of human perception along with a simple depth approximation algorithm to generate non-photorealistic renditions that would be difficult to achieve with existing methods. Once a perceptually plausible depth map is obtained from the input image, we show how simple algorithms yield powerful new depictions of such an image. Additionally, we show how artistic manipulation of depth maps can be used to create novel non-photorealistic versions, for which we provide the user with an intuitive interface. Our real-time implementation on graphics hardware allows the user to efficiently explore artistic possibilities for each image. We show results produced with six different styles proving the versatility of our approach, and validate our assumptions and simplifications by means of a user study.

Separable Subsurface Scattering

In this paper, we propose two real‐time models for simulating subsurface scattering for a large variety of translucent materials, which need under 0.5 ms per frame to execute. This makes them a practical option for real‐time production scenarios. Current state‐of‐the‐art, real‐time approaches simulate subsurface light transport by approximating the radially symmetric non‐separable diffusion kernel with a sum of separable Gaussians, which requires multiple (up to 12) 1D convolutions. In this work we relax the requirement of radial symmetry to approximate a 2D diffuse reflectance profile by a single separable kernel. We first show that low‐rank approximations based on matrix factorization outperform previous approaches, but they still need several passes to get good results. To solve this, we present two different separable models: the first one yields a high‐quality diffusion simulation, while the second one offers an attractive trade‐off between physical accuracy and artistic control. Both allow rendering of subsurface scattering using only two 1D convolutions, reducing both execution time and memory consumption, while delivering results comparable to techniques with higher cost. Using our importance‐sampling and jittering strategies, only seven samples per pixel are required. Our methods can be implemented as simple post‐processing steps without intrusive changes to existing rendering pipelines.

Separable subsurface scattering

Due to the parallel advances in hardware and software, graphics in games are continuously improving. Still, for a 60-fps game, everything contained in a frame must be computed in just about 16 milliseconds. Given this tight time budget, certain effects cannot be computed and are simply not simulated, sacrificing realism to reallocate resources to other aspects of the game. This demo shows a technique to simulate subsurface scattering for human skin that runs in just over one millisecond per frame, making it a practical option for even the most challenging game scenarios. Previous real-time approaches simulate it by approximating the non-separable diffusion kernel using a sum of Gaussians, which require several (usually six) 1D convolutions. The proposed technique decomposes the exact 2D diffusion kernel with only two 1D functions, which allows subsurface scattering rendering with only two convolutions, reducing both time and memory without a decrease in quality. The 1D functions are defined in an intuitive way with just three parameters, allowing for easy edits.