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We present an efficient algorithm for visualizing the effect of black holes on its distant surroundings as seen from an observer nearby in orbit. Our solution is GPU-based and builds upon a two-step approach, where we first derive an adaptive grid to map the 360-view around the observer to the distorted celestial sky, which can be directly reused for different camera orientations. Using a grid, we can rapidly trace rays back to the observer through the distorted spacetime, avoiding the heavy workload of standard tracing solutions at real-time rates. By using a novel interpolation technique we can also simulate an observer path by smoothly transitioning between multiple grids. Our approach accepts real star catalogues and environment maps of the celestial sky and generates the resulting black-hole deformations in real time.

t-distributed Stochastic Neighbour Embedding (t-SNE) has become a standard for exploratory data analysis, as it is capable of revealing clusters even in complex data while requiring minimal user input. While its run-time complexity limited it to small datasets in the past, recent efforts improved upon the expensive similarity computations and the previously quadratic minimization. Nevertheless, t-SNE still has high runtime and memory costs when operating on millions of points. We present a novel method for executing the t-SNE minimization. While our method overall retains a linear runtime complexity, we obtain a significant performance increase in the most expensive part of the minimization. We achieve a significant improvement without a noticeable decrease in accuracy even when targeting a 3D embedding. Our method constructs a pair of spatial hierarchies over the embedding, which are simultaneously traversed to approximate many N-body interactions at once. We demonstrate an efficient GPGPU implementation and evaluate its performance against state-of-the-art methods on a variety of datasets.

In recent years the t-distributed Stochastic Neighbor Embedding (t-SNE) algorithm has become one of the most used and insightful techniques for exploratory data analysis of high-dimensional data. It reveals clusters of high-dimensional data points at different scales while only requiring minimal tuning of its parameters. However, the computational complexity of the algorithm limits its application to relatively small datasets. To address this problem, several evolutions of t-SNE have been developed in recent years, mainly focusing on the scalability of the similarity computations between data points. However, these contributions are insufficient to achieve interactive rates when visualizing the evolution of the t-SNE embedding for large datasets. In this work, we present a novel approach to the minimization of the t-SNE objective function that heavily relies on graphics hardware and has linear computational complexity. Our technique decreases the computational cost of running t-SNE on datasets by orders of magnitude and retains or improves on the accuracy of past approximated techniques. We propose to approximate the repulsive forces between data points by splatting kernel textures for each data point. This approximation allows us to reformulate the t-SNE minimization problem as a series of tensor operations that can be efficiently executed on the graphics card. An efficient implementation of our technique is integrated and available for use in the widely used Google TensorFlow.js, and an open-source C++ library.

Light scattering in participating media is a natural phenomenon that is increasingly featured in movies and games, as it is visually pleasing and lends realism to a scene. In art, it may further be used to express a certain mood or emphasize objects. Here, artists often rely on stylization when creating scattering effects, not only because of the complexity of physically correct scattering, but also to increase expressiveness. Little research, however, focuses on artistically influencing the simulation of the scattering process in a virtual 3D scene. We propose novel stylization techniques, enabling artists to change the appearance of single scattering effects such as light shafts. Users can add, remove, or enhance light shafts using occluder manipulation. The colors of the light shafts can be stylized and animated using easily modifiable transfer functions. Alternatively, our system can optimize a light map given a simple user input for a number of desired views in the 3D world. Finally, we enable artists to control the heterogeneity of the underlying medium. Our stylized scattering solution is easy to use and compatible with standard rendering pipelines. It works for animated scenes and can be executed in real time to provide the artist with quick feedback.

Parallel Coordinate Plots (PCPs) is one of the most powerful techniques for the visualization of multivariate data. However, for large datasets, the representation suffers from clutter due to overplotting. In this case, discerning the underlying data information and selecting specific interesting patterns can become difficult. We propose a new and simple technique to improve the display of PCPs by emphasizing the underlying data structure. Our Orientation-enhanced Parallel Coordinate Plots (OPCPs) improve pattern and outlier discernibility by visually enhancing parts of each PCP polyline with respect to its slope. This enhancement also allows us to introduce a novel and efficient selection method, the Orientation-enhanced Brushing (O-Brushing). Our solution is particularly useful when multiple patterns are present or when the view on certain patterns is obstructed by noise. We present the results of our approach with several synthetic and real-world datasets. Finally, we conducted a user evaluation, which verifies the advantages of the OPCPs in terms of discernibility of information in complex data. It also confirms that O-Brushing eases the selection of data patterns in PCPs and reduces the amount of necessary user interactions compared to state-of-the-art brushing techniques.

Motion blur in a photo is the consequence of object motion during the image acquisition. It results in a visible trail along the motion of a recorded object and can be used by photographers to convey a sense of motion. Nevertheless, it is very challenging to acquire this effect as intended and requires much experience from the photographer. To achieve actual control over the motion blur, one could be added in a post process but current solutions require complex manual intervention and can lead to artifacts that mix moving and static objects incorrectly. In this paper, we propose a novel method to add motion blur to a single image that generates the illusion of a photographed motion. Relying on a minimal user input, a filtering process is employed to produce a virtual motion effect. It carefully handles object boundaries to avoid artifacts produced by standard filtering methods. We illustrate the effectiveness of our solution with various complex examples, including multi-directional blur, reflections, multiple objects, and illustrate how several motion-related artistic effects can be achieved. Our post-processing solution is an alternative to capturing the intended real-world motion blur directly and enables fine-grained control of the motion-blur effect.

We propose the computation of a perceptual motion blur in videos. Our technique takes the predicted eye motion into account when watching the video. Compared to traditional motion blur recorded by a video camera our approach results in a perceptual blur that is closer to reality. This postprocess can also be used to simulate different shutter effects or for other artistic purposes. It handles real and artificial video input, is easy to compute and has a low additional cost for rendered content. We illustrate its advantages in a user study using eye tracking.

Stochastically solving the rendering integral (particularly visibility) is the de-facto standard for physically-based light transport but it is computationally expensive, especially when displaying heterogeneous volumetric data. In this work, we present efficient techniques to speed-up the rendering process via a novel visibility-estimation method in concert with an unbiased importance sampling (involving environmental lighting and visibility inside the volume), filtering, and update techniques for both static and animated scenes. Our major contributions include a progressive estimate of partial occlusions based on a fast sweeping-plane algorithm. These occlusions are stored in an octahedral representation, which can be conveniently transformed into a quadtree-based hierarchy suited for a joint importance sampling. Further, we propose sweep-space filtering, which suppresses the occurrence of fireflies and investigate different update schemes for animated scenes. Our technique is unbiased, requires little precomputation, is highly parallelizable, and is applicable to a various volume data sets, dynamic transfer functions, animated volumes and changing environmental lighting.

Height fields have become an important element of realistic real-time image synthesis to represent surface details. In this paper, we focus on the frequent case of static height-field data, for which we can precompute acceleration structures. While many rendering algorithms exist that impose tradeoffs between speed and accuracy, we show that even accurate rendering can be combined with high performance. A careful analysis of the surface defined by the height values, leads to an efficient and accurate precomputation method. As a result, each texel stores a safety shape inside which a ray cannot cross the surface twice. This property ensures that no intersections are missed during the efficient marching method. Our analysis is general and can even consider visibility constraints that are robustly integrated into the precomputation. Further, we propose a particular instance of safety shapes with little memory overhead, which results in a rendering algorithm that outperforms existing methods, both in terms of accuracy and performance.

International audience; Clip art is a simplified illustration form consisting of layered filled polygons or closed curves used to convey 3-D shape information in a 2-D vector graphics format. This paper focuses on the problem of direct conversion of smooth surfaces, ranging from the free-form shapes of art and design to the mathematical structures of geometry and topology, into a clip art form suitable for illustration use in books, papers and presentations. We show how to represent silhouette, shadow, gleam and other surface feature curves as the intersection of implicit surfaces, and derive equations for their efficient interrogation via particle chains. We further describe how to sort, orient, identify and fill the closed regions that overlay to form clip art. We demonstrate the results with numerous renderings used to illustrate the paper itself. More at http://artis.imag.fr/Publications/2008/SEH08/