Martin Weier

Perception-driven Accelerated Rendering

Advances in computer graphics enable us to create digital images of astonishing complexity and realism. However, processing resources are still a limiting factor. Hence, many costly but desirable aspects of realism are often not accounted for, including global illumination, accurate depth of field and motion blur, spectral effects, etc. especially in real‐time rendering. At the same time, there is a strong trend towards more pixels per display due to larger displays, higher pixel densities or larger fields of view. Further observable trends in current display technology include more bits per pixel (high dynamic range, wider color gamut/fidelity), increasing refresh rates (better motion depiction), and an increasing number of displayed views per pixel (stereo, multi‐view, all the way to holographic or lightfield displays). These developments cause significant unsolved technical challenges due to aspects such as limited compute power and bandwidth. Fortunately, the human visual system has certain limitations, which mean that providing the highest possible visual quality is not always necessary. In this report, we present the key research and models that exploit the limitations of perception to tackle visual quality and workload alike. Moreover, we present the open problems and promising future research targeting the question of how we can minimize the effort to compute and display only the necessary pixels while still offering a user full visual experience.

Foveated real-time ray tracing for head-mounted displays

Head‐mounted displays with dense pixel arrays used for virtual reality applications require high frame rates and low latency rendering. This forms a challenging use case for any rendering approach. In addition to its ability of generating realistic images, ray tracing offers a number of distinct advantages, but has been held back mainly by its performance. In this paper, we present an approach that significantly improves image generation performance of ray tracing. This is done by combining foveated rendering based on eye tracking with reprojection rendering using previous frames in order to drastically reduce the number of new image samples per frame. To reproject samples a coarse geometry is reconstructed from a G‐Buffer. Possible errors introduced by this reprojection as well as parts that are critical to the perception are scheduled for resampling. Additionally, a coarse color buffer is used to provide an initial image, refined smoothly by more samples were needed. Evaluations and user tests show that our method achieves real‐time frame rates, while visual differences compared to fully rendered images are hardly perceivable. As a result, we can ray trace non‐trivial static scenes for the Oculus DK2 HMD at 1182 × 1464 per eye within the the VSync limits without perceived visual differences.

An analysis of eye-tracking data in foveated ray tracing

We present an analysis of eye tracking data produced during a quality-focused user study of our own foveated ray tracing method. Generally, foveated rendering serves the purpose of adapting actual rendering methods to a user’s gaze. This leads to performance improvements which also allow for the use of methods like ray tracing, which would be computationally too expensive otherwise, in fields like virtual reality (VR), where high rendering performance is important to achieve immersion, or fields like scientific and information visualization, where large amounts of data may hinder real-time rendering capabilities. We provide an overview of our rendering system itself as well as information about the data we collected during the user study, based on fixation tasks to be fulfilled during flights through virtual scenes displayed on a head-mounted display (HMD). We analyze the tracking data regarding its precision and take a closer look at the accuracy achieved by participants when focusing the fixation targets. This information is then put into context with the quality ratings given by the users, leading to a surprising relation between fixation accuracy and quality ratings.

RaTrace: simple and efficient abstractions for BVH ray traversal algorithms

In order to achieve the highest possible performance, the ray traversal and intersection routines at the core of every high-performance ray tracer are usually hand-coded, heavily optimized, and implemented separately for each hardware platform—even though they share most of their algorithmic core. The results are implementations that heavily mix algorithmic aspects with hardware and implementation details, making the code non-portable and difficult to change and maintain. In this paper, we present a new approach that offers the ability to define in a functional language a set of conceptual, high-level language abstractions that are optimized away by a special compiler in order to maximize performance. Using this abstraction mechanism we separate a generic ray traversal and intersection algorithm from its low-level aspects that are specific to the target hardware. We demonstrate that our code is not only significantly more flexible, simpler to write, and more concise but also that the compiled results perform as well as state-of-the-art implementations on any of the tested CPU and GPU platforms.

Guided High-Quality Rendering

We present a system which allows for guiding the image quality in global illumination (GI) methods by user-specified regions of interest (ROIs). This is done with either a tracked interaction device or a mouse-based method, making it possible to create a visualization with varying convergence rates throughout one image towards a GI solution. To achieve this, we introduce a scheduling approach based on Sparse Matrix Compression (SMC) for efficient generation and distribution of rendering tasks on the GPU that allows for altering the sampling density over the image plane. Moreover, we present a prototypical approach for filtering the newly, possibly sparse samples to a final image. Finally, we show how large-scale display systems can benefit from rendering with ROIs.

Efficient Strategies for Acceleration Structure Updates in Interactive Ray Tracing Applications on the Cell Processor

We present fast complete rebuild strategies, as well as adapted intelligent local update strategies for acceleration data structures for interactive ray tracing environments. Both approaches can be combined. Although the proposed strategies could be used with other data structures and architectures as well, they are currently tailored to the Bounding Interval Hierarchy on the Cell chip.

Predicting the gaze depth in head-mounted displays using multiple feature regression

Head-mounted displays (HMDs) with integrated eye trackers have opened up a new realm for gaze-contingent rendering. The accurate estimation of gaze depth is essential when modeling the optical capabilities of the eye. Most recently multifocal displays are gaining importance, requiring focus estimates to control displays or lenses. Deriving the gaze depth solely by sampling the scenes depth at the point-of-regard fails for complex or thin objects as eye tracking is suffering from inaccuracies. Gaze depth measures using the eyes vergence only provide an accurate depth estimate for the first meter. In this work, we combine vergence measures and multiple depth measures into feature sets. This data is used to train a regression model to deliver improved estimates. We present a study showing that using multiple features allows for an accurate estimation of the focused depth (MSE<0.1m) over a wide range (first 6m).

Foveated Depth-of-Field Filtering in Head-Mounted Displays

In recent years, a variety of methods have been introduced to exploit the decrease in visual acuity of peripheral vision, known as foveated rendering. As more and more computationally involved shading is requested and display resolutions increase, maintaining low latencies is challenging when rendering in a virtual reality context. Here, foveated rendering is a promising approach for reducing the number of shaded samples. However, besides the reduction of the visual acuity, the eye is an optical system, filtering radiance through lenses. The lenses create depth-of-field (DoF) effects when accommodated to objects at varying distances. The central idea of this article is to exploit these effects as a filtering method to conceal rendering artifacts. To showcase the potential of such filters, we present a foveated rendering system, tightly integrated with a gaze-contingent DoF filter. Besides presenting benchmarks of the DoF and rendering pipeline, we carried out a perceptual study, showing that rendering quality is rated almost on par with full rendering when using DoF in our foveated mode, while shaded samples are reduced by more than 69%.

Foveated depth-of-field filtering in head-mounted displays

In recent years, a variety of methods have been introduced to exploit the decrease in visual acuity of peripheral vision, known as foveated rendering. As more and more computationally involved shading is requested and display resolutions increase, maintaining low latencies is challenging when rendering in a virtual reality context. Here, foveated rendering is a promising approach for reducing the number of shaded samples. However, besides the reduction of the visual acuity, the eye is an optical system, filtering radiance through lenses. The lenses create depth-of-field (DoF) effects when accommodated to objects at varying distances. The central idea of this article is to exploit these effects as a filtering method to conceal rendering artifacts. To showcase the potential of such filters, we present a foveated rendering system, tightly integrated with a gaze-contingent DoF filter. Besides presenting benchmarks of the DoF and rendering pipeline, we carried out a perceptual study, showing that rendering quality is rated almost on par with full rendering when using DoF in our foveated mode, while shaded samples are reduced by more than 69%.

Containerized Distributed Rendering for Interactive Environments

Development and rapid prototyping for large interactive environments like tiled-display walls pose many challenges. One is the heterogeneity of the various applications and libraries. A visual application tailored for a single monitor setup with a certain software environment is difficult to port and distribute to a multi-display, multi-PC setup. As a solution to this problem, we explore the potential of lightweight containerization techniques for distributed interactive applications. In particular, we present how the necessary runtime and build environments including libraries and drivers can be abstracted using the Docker framework. We demonstrate the packing of an existing single-machine GPU-enabled ray tracer inside a container to be used on tiled display walls. The performance measurements reveal that the containerization has a negligible impact on the system’s performance but allows for easy setup, integration, and distribution of complex applications.