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Eye-tracking with gaze estimation is a key element in many applications, ranging from foveated rendering and user interaction to behavioural analysis and usage metrics. For virtual reality, eye-tracking typically relies on near-eye cameras that are mounted in the VR headset. Such methods usually involve an initial calibration to create a mapping from eye features to a gaze position. However, the accuracy based on the initial calibration degrades when the position of the headset relative to the users’ head changes; this is especially noticeable when users readjust the headset for comfort or even completely remove it for a short while. We show that a correction of such shifts can be achieved via 2D drift vectors in eye space. Our method estimates these drifts by extracting salient cues from the shown virtual environment to determine potential gaze directions. Our solution can compensate for HMD shifts, even those arising from taking off the headset, which enables us to eliminate reinitialization steps.

Ambient occlusion (AO) is a popular rendering technique that enhances depth perception and realism by darkening locations that are less exposed to ambient light (e.g., corners and creases). In real-time applications, screen-space variants, relying on the depth buffer, are used due to their high performance and good visual quality. However, these only take visible surfaces into account, resulting in inconsistencies, especially during motion. Stochastic-Depth Ambient Occlusion is a novel AO algorithm that accounts for occluded geometry by relying on a stochastic depth map, capturing multiple scene layers per pixel at random. Hereby, we efficiently gather missing information in order to improve upon the accuracy and spatial stability of conventional screen-space approximations, while maintaining real-time performance. Our approach integrates well into existing rendering pipelines and improves the robustness of many different AO techniques, including multi-view solutions.

Monte-Carlo rendering requires determining the visibility between scene points as the most common and compute intense operation to establish paths between camera and light source. Unfortunately, many tests reveal occlusions and the corresponding paths do not contribute to the final image. In this work, we present next event estimation++ (NEE++): a visibility mapping technique to perform visibility tests in a more informed way by caching voxel to voxel visibility probabilities. We show two scenarios: Russian roulette style rejection of visibility tests and direct importance sampling of the visibility. We show applications to next event estimation and light sampling in a uni-directional path tracer, and light-subpath sampling in Bi-Directional Path Tracing. The technique is simple to implement, easy to add to existing rendering systems, and comes at almost no cost, as the required information can be directly extracted from the rendering process itself. It discards up to 80% of visibility tests on average, while reducing variance by 20% compared to other state-of-the-art light sampling techniques with the same number of samples. It gracefully handles complex scenes with efficiency similar to Metropolis light transport techniques but with a more uniform convergence.

Stereoscopic 3D technology gives visual content creators a new dimension of design when creating images and movies. While useful for conveying emotion, laying emphasis on certain parts of the scene, or guiding the viewer's attention, editing stereo content is a challenging task. Not respecting comfort zones or adding incorrect depth cues, for example depth inversion, leads to a poor viewing experience. In this paper, we present a solution for editing stereoscopic content that allows an artist to impose disparity constraints and removes resulting depth conflicts using an optimization scheme. Using our approach, an artist only needs to focus on important high-level indications that are automatically made consistent with the entire scene while avoiding contradictory depth cues and respecting viewer comfort.

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.

Light painting is an artform where a light source is moved during a long-exposure shot, creating trails resembling a stroke on a canvas. It is very difficult to perform because the light source needs to be moved at the intended speed and along a precise trajectory. Additionally, images can be corrupted by the person moving the light. We propose computational light painting, which avoids such artifacts and is easy to use. Taking a video of the moving light as input, a virtual exposure allows us to draw the intended light positions in a post-process. We support animation, as well as 3D light sculpting, with high-quality results.

We propose a novel framework for photometric stereo (PS) under low-light conditions using uncalibrated near-light illumination. It operates on free-form video sequences captured with a minimalistic and affordable setup. We address issues such as albedo variations, shadowing, perspective projections, and camera noise. Our method uses specular spheres detected with a perspective-correcting Hough transform to robustly triangulate light positions in the presence of outliers via a least-squares approach. Furthermore, we propose an iterative reweighting scheme in combination with an $\ell _{p}$ -norm minimizer to robustly solve the calibrated near-light PS problem. In contrast to other approaches, our framework reconstructs depth, albedo (relative to light source intensity), and normals simultaneously and is demonstrated on synthetic and real-world scenes.

The quality of shadow mapping is traditionally limited by texture resolution. We present a novel lossless compression scheme for high-resolution shadow maps based on precomputed multiresolution hierarchies. Traditional multiresolution trees can compactly represent homogeneous regions of shadow maps at coarser levels, but require many nodes for fine details. By conservatively adapting the depth map, we can significantly reduce the tree complexity. Our proposed method offers high compression rates, avoids quantization errors, exploits coherency along all data dimensions, and is well-suited for GPU architectures. Our approach can be applied for coherent shadow maps as well, enabling several applications, including high-quality soft shadows and dynamic lights moving on fixed-trajectories.

Voxel-based approaches are today's standard to encode volume data. Recently, directed acyclic graphs (DAGs) were successfully used for compressing sparse voxel scenes as well, but they are restricted to a single bit of (geometry) information per voxel. We present a method to compress arbitrary data, such as colors, normals, or reflectance information. By decoupling geometry and voxel data via a novel mapping scheme, we are able to apply the DAG principle to encode the topology, while using a palette-based compression for the voxel attributes, leading to a drastic memory reduction. Our method outperforms existing state-of-the-art techniques and is well-suited for GPU architectures. We achieve real-time performance on commodity hardware for colored scenes with up to 17 hierarchical levels (a 128K3 voxel resolution), which are stored fully in core.

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 present a novel pipeline to generate a depth map from a single image that can be used as input for a variety of artistic depth-based effects. In such a context, the depth maps do not have to be perfect but are rather designed with respect to a desired result. Consequently, our solution centers around user interaction and relies on a scribble-based depth editing. The annotations can be sparse, as the depth map is generated by a diffusion process, which is guided by image features. We support a variety of controls, such as a non-linear depth mapping, a steering mechanism for the diffusion (e.g., directionality, emphasis, or reduction of the influence of image cues), and besides absolute, we also support relative depth indications. In case that a depth estimate is available from an automatic solution, we illustrate how this information can be integrated in form of a depth palette, that allows the user to transfer depth values via a painting metaphor. We demonstrate a variety of artistic 3D results, including wiggle stereoscopy, artistic abstractions, haze, unsharp masking, and depth of field.

When human luminance perception operates close to its absolute threshold, i. e., the lowest perceivable absolute values, appearance changes substantially compared to common photopic or scotopic vision. In particular, most observers report perceiving temporally-varying noise. Two reasons are physiologically plausible; quantum noise (due to the low absolute number of photons) and spontaneous photochemical reactions. Previously, static noise with a normal distribution and no account for absolute values was combined with blue hue shift and blur to simulate scotopic appearance on a photopic display for movies and interactive applications (e.g., games). We present a computational model to reproduce the specific distribution and dynamics of "scotopic noise" for specific absolute values. It automatically introduces a perceptually-calibrated amount of noise for a specific luminance level and supports animated imagery. Our simulation runs in milliseconds at HD resolution using graphics hardware and favorably compares to simpler alternatives in a perceptual experiment.

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.

Purpose Computer-assisted orthopedic surgery aims at minimizing invasiveness, postoperative pain, and morbidity with computer-assisted preoperative planning and intra-operative guidance techniques, of which camera-based navigation and patient-specific templates (PST) are the most common. PSTs are one-time templates that guide the surgeon initially in cutting slits or drilling holes. This method can be extended to reusable and customizable surgical guides (CSG), which can be adapted to the patients’ bone. Determining the right set of CSG input parameters by hand is a challenging task, given the vast amount of input parameter combinations and the complex physical interaction between the PST/CSG and the bone. Methods This paper introduces a novel algorithm to solve the problem of choosing the right set of input parameters. Our approach predicts how well a CSG instance is able to reproduce the planned alignment based on a physical simulation and uses a genetic optimization algorithm to determine optimal configurations. We validate our technique with a prototype of a pin-based CSG and nine rapid prototyped distal femora. Results The proposed optimization technique has been compared to manual optimization by experts, as well as participants with domain experience. Using the optimization technique, the alignment errors remained within practical boundaries of 1.2 mm translation and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$0.9^\circ $$\end{document}0.9∘ rotation error. In all cases, the proposed method outperformed manual optimization. Conclusions Manually optimizing CSG parameters turns out to be a counterintuitive task. Even after training, subjects with and without anatomical background fail in choosing appropriate CSG configurations. Our optimization algorithm ensures that the CSG is configured correctly, and we could demonstrate that the intended alignment of the CSG is accurately reproduced on all tested bone geometries.

Immersive displays allow presentation of rich video content over a wide field of view. We present a method to boost visual importance for a selected - possibly invisible - scene part in a cluttered virtual environment. This desirable feature enables to unobtrusively guide the gaze direction of a user to any location within the immersive 360° surrounding. Our method is based on subtle gaze direction which did not include head rotations in previous work. For covering the full 360° environment and wide field of view, we contribute an approach for dynamic stimulus positioning and shape variation based on eccentricity to compensate for visibility differences across the visual field. Our approach is calibrated in a perceptual study for a head-mounted display with binocular eye tracking. An additional study validates the method within an immersive visual search task.

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.

Conventional depth video compression uses video codecs designed for color images. Given the performance of current encoding standards, this solution seems efficient. However, such an approach suffers from many issues stemming from discrepancies between depth and light perception. To exploit the inherent limitations of human depth perception, we propose a novel depth compression method that employs a disparity perception model. In contrast to previous methods, we account for disparity masking, and model a distinct relation between depth perception and contrast in luminance. Our solution is a natural extension to the H.264 codec and can easily be integrated into existing decoders. It significantly improves both the compression efficiency without sacrificing visual quality of depth of rendered content, and the output of depth-reconstruction algorithms or depth cameras.

Binocular disparity is one of the most important depth cues used by the human visual system. Recently developed stereo-perception models allow us to successfully manipulate disparity in order to improve viewing comfort, depth discrimination as well as stereo content compression and display. Nonetheless, all existing models neglect the substantial influence of luminance on stereo perception. Our work is the first to account for the interplay of luminance contrast (magnitude/frequency) and disparity and our model predicts the human response to complex stereo-luminance images. Besides improving existing disparity-model applications (e.g., difference metrics or compression), our approach offers new possibilities, such as joint luminance contrast and disparity manipulation or the optimization of auto-stereoscopic content. We validate our results in a user study, which also reveals the advantage of considering luminance contrast and its significant impact on disparity manipulation techniques., National Science Foundation (U.S.) (CGV-1111415)

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.

Nowadays, there is a strong trend towards rendering to higher-resolution displays and at high frame rates. This development aims at delivering more detail and better accuracy, but it also comes at a significant cost. Although graphics cards continue to evolve with an ever-increasing amount of computational power, the speed gain is easily counteracted by increasingly complex and sophisticated shading computations. For real-time applications, the direct consequence is that image resolution and temporal resolution are often the first candidates to bow to the performance constraints (e.g. although full HD is possible, PS3 and XBox often render at lower resolutions). In order to achieve high-quality rendering at a lower cost, one can exploit temporal coherence (TC). The underlying observation is that a higher resolution and frame rate do not necessarily imply a much higher workload, but a larger amount of redundancy and a higher potential for amortizing rendering over several frames. In this survey, we investigate methods that make use of this principle and provide practical and theoretical advice on how to exploit TC for performance optimization. These methods not only allow incorporating more computationally intensive shading effects into many existing applications, but also offer exciting opportunities for extending high-end graphics applications to lower-spec consumer-level hardware. To this end, we first introduce the notion and main concepts of TC, including an overview of historical methods. We then describe a general approach, image-space reprojection, with several implementation algorithms that facilitate reusing shading information across adjacent frames. We also discuss data-reuse quality and performance related to reprojection techniques. Finally, in the second half of this survey, we demonstrate various applications that exploit TC in real-time rendering. © 2012 Wiley Periodicals, Inc.

This work proposes a technique to transfer the material style or mood from a guide source such as an image or video onto a target 3D scene. It formulates the problem as a combinatorial optimization of assigning discrete materials extracted from the guide source to discrete objects in the target 3D scene. The assignment is optimized to fulfill multiple goals: overall image mood based on several image statistics; spatial material organization and grouping as well as geometric similarity between objects that were assigned to similar materials. To be able to use common uncalibrated images and videos with unknown geometry and lighting as guides, a material estimation derives perceptually plausible reflectance, specularity, glossiness, and texture. Finally, results produced by our method are compared to manual material assignments in a perceptual study. © 2012 Wiley Periodicals, Inc.

Afterimages are optical illusions, particularly well perceived when fixating an image for an extended period of time and then looking at a neutral background, where an inverted copy of the original stimulus appears. The full mechanism that produces the perceived specific colors and shapes is complex and not entirely understood, but most of the important attributes can be well explained by bleaching of retinal photoreceptors (retinal kinetics). We propose a model to compute afterimages that allows us to simulate their temporal, color and time-frequency behavior. Using this model, high dynamic range (HDR) content can be processed to add realistic afterimages to low dynamic range (LDR) media. Hereby, our approach helps in conveying the original source's luminance and contrast. It can be applied in real-time on full-HD HDR content using standard graphics hardware. Finally, our approach is validated in a perceptual study. © 2012 Wiley Periodicals, Inc.

We propose an algorithm to compute interactive indirect illumination in dynamic scenes containing millions of triangles. It makes use of virtual point lights (VPL) to compute bounced illumination and a point-based scene representation to query indirect visibility, similar to Imperfect Shadow Maps (ISM). To ensure a high fidelity of indirect light and shadows, our solution is made view-adaptive by means of two orthogonal improvements: First, the VPL distribution is chosen to provide more detail, that is, more dense VPL sampling, where these contribute most to the current view. Second, the scene representation for indirect visibility is adapted to ensure geometric detail where it affects indirect shadows in the current view.

Level-of-Detail structures are a key component for scalable rendering. Built from raw 3D data, these structures are often defined as Bounding Volume Hierarchies, providing coarse-to-fine adaptive approximations that are well-adapted for many-view rasterization. Here, the total number of pixels in each view is usually low, while the cost of choosing the appropriate LoD for each view is high. This task represents a challenge for existing GPU algorithms. We propose ManyLoDs, a new GPU algorithm to efficiently compute many LoDs from a Bounding Volume Hierarchy in parallel by balancing the workload within and among LoDs. Our approach is not specific to a particular rendering technique, can be used on lazy representations such as polygon soups, and can handle dynamic scenes. We apply our method to various many-view rasterization applications, including Instant Radiosity, Point-Based Global Illumination, and reflection / refraction mapping. For each of these, we achieve real-time performance in complex scenes at high resolutions.

High-refresh-rate displays (e. g., 120 Hz) have recently become available on the consumer market and quickly gain on popularity. One of their aims is to reduce the perceived blur created by moving objects that are tracked by the human eye. However, an improvement is only achieved if the video stream is produced at the same high refresh rate (i. e. 120 Hz). Some devices, such as LCD TVs, solve this problem by converting low-refresh-rate content (i. e. 50 Hz PAL) into a higher temporal resolution (i. e. 200 Hz) based on two-dimensional optical flow. In our approach, we will show how rendered three-dimensional images produced by recent graphics hardware can be up-sampled more efficiently resulting in higher quality at the same time. Our algorithm relies on several perceptual findings and preserves the naturalness of the original sequence. A psychophysical study validates our approach and illustrates that temporally up-sampled video streams are preferred over the standard low-rate input by the majority of users. We show that our solution improves task performance on high-refresh-rate displays.

We present a GPU-based real-time rendering method that simulates high-quality depth-of-field effects, similar in quality to multiview accumulation methods. Most real-time approaches have difficulties to obtain good approximations of visibility and view-dependent shading due to the use of a single view image. Our method also avoids the multiple rendering of a scene, but can approximate different views by relying on a layered image-based scene representation. We present several performance and quality improvements, such as early culling, approximate cone tracing, and jittered sampling. Our method achieves artifact-free results for complex scenes and reasonable depth-of-field blur in real time.

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/

Immersion is the ultimate goal of head-mounted displays (HMD) for Virtual Reality (VR) in order to produce a convincing user experience. Two important aspects in this context are motion sickness, often due to imprecise calibration, and the integration of a reliable eye tracking. We propose an affordable hard- and software solution for drift-free eye-tracking and user-friendly lens calibration within an HMD. The use of dichroic mirrors leads to a lean design that provides the full field-of-view (FOV) while using commodity cameras for eye tracking. Our prototype supports personalizable lens positioning to accommodate for different interocular distances. On the software side, a model-based calibration procedure adjusts the eye tracking system and gaze estimation to varying lens positions. Challenges such as partial occlusions due to the lens holders and eye lids are handled by a novel robust monocular pupil-tracking approach. We present four applications of our work: Gaze map estimation, foveated rendering for depth of field, gaze-contingent level-of-detail, and gaze control of virtual avatars.

We accelerate volumetric obscurance, a variant of ambient occlusion, and solve undersampling artifacts, such as banding, noise or blurring, that screen-space techniques traditionally suffer from. We make use of an efficient statistical model to evaluate the occlusion factor in screen-space using a single sample. Overestimations and halos are reduced by an adaptive layering of the visible geometry. Bias at tilted surfaces is avoided by projecting and evaluating the volumetric obscurance in tangent space of each surface point. We compare our approach to several traditional screen-space ambient obscurance techniques and show its competitive qualitative and quantitative performance. Our algorithm maps well to graphics hardware, does not require the traditional bilateral blur step of previous approaches, and avoids typical screen-space related artifacts such as temporal instability due to undersampling.

We present a complete hardware and software solution for integrating binocular eye tracking into current state-of-the-art lens-based Head-mounted Displays (HMDs) without affecting the user's wide field-of-view off the display. The system uses robust and efficient new algorithms for calibration and pupil tracking and allows realtime eye tracking and gaze estimation. Estimating the relative gaze direction of the user opens the door to a much wider spectrum of virtual reality applications and games when using HMDs. We show a 3d-printed prototype of a low-cost HMD with eye tracking that is simple to fabricate and discuss a variety of VR applications utilizing gaze estimation.

International audience; The chromostereopsis phenomenom leads to a differing depth perception of different color hues, e.g., red is perceived slightly in front of blue. In chromostereoscopic rendering 2D images are produced that encode depth in color. While the natural chromostereopsis of our human visual system is rather low, it can be enhanced via ChromaDepth®glasses, which induce chromatic aberrations in one eye by refracting light of different wavelengths differently, hereby offsetting the projected position slightly in one eye. Although, it might seem natural to map depth linearly to hue, which was also the basis of previous solutions, we demonstrate that such a mapping reduces the stereoscopic effect when using standard trichromatic displays or printing systems. We propose an algorithm, which enables an improved stereoscopic experience with reduced artifacts.

Volumetric light scattering is a complex phenomenon that is difficult to simulate in real time as light can be scattered towards the camera from everywhere in space. By assuming a single-scattering model, we can transform the usually-employed ray-marching into an efficient ray-independent texture filtering process. Our algorithm builds upon a rectified shadow map as input and we propose an efficient rectification scheme, which could be used by other approaches as well. The resulting scattering method is very fast and almost independent of the screen resolution, but it still produces near-reference results. These properties make it a good candidate for performance-critical applications, such as games.

International audience; In a standard desktop environment a mouse has proven to be an efficient interaction device. However, when working with stereoscopic content, the shape and behavior of a standard 2D mouse cursor is not suitable, as depth conflicts between the cursor and the content can lead to confusion. In this paper, we show that specific 3D cursors can increase accuracy and user comfort. We first discuss several situations in which traditional cursors fail and explain their limitations and shortcomings. Based on these observations, we propose new mouse cursors that are designed for the use in a stereoscopic environment. In particular, we investigate the integration of the cursor in the scene in terms of occlusion, depth matching and shape and propose a new cursor that adapts to the 3D scene. We conducted an experiment to investigate accuracy, speed and comfort of the various interaction solutions.

Compressed sensing (CS) magnetic resonance imaging (MRI) enables the reconstruction of MRI images with fewer samples in k-space. One requirement is that the acquired image has a sparse representation in a known transform domain. MR angiograms are already sparse in the image domain. They can be further sparsified through finite-differences. Therefore, it is a natural application for CS-MRI. However, low-contrast vessels are likely to disappear at high undersampling ratios, since the commonly used £1 reconstruction tends to underestimate the magnitude of the transformed sparse coefficients. These vessels, however, are likely to be clinically important for medical diagnosis. To avoid the fading of low-contrast vessels, we propose a user-guided CS MRI that is able to mitigate the reduction of vessel contrast within a region of interest (ROI). Simulations show that these low-contrast vessels can be well maintained via our method which results in higher local quality compared to conventional CS.

International audience; Although volumetric phenomena are important for realistic rendering and can even be a crucial component in the image, the artistic control of the volume's appearance is challenging. Appropriate tools to edit volume properties are missing, which can make it necessary to use simulation results directly. Alternatively, high-level modifications that are rarely intuitive, e.g., the tweaking of noise function parameters, can be utilized. Our work introduces a solution to stylize single-scattering volumetric effects in static volumes. Hereby, an artistic and intuitive control of emission, scattering and extinction becomes possible, while ensuring a smooth and coherent appearance when changing the viewpoint. Our method is based on tomographic reconstruction,which we link to the volumetric rendering equation. It analyzes a number of target views provided by the artist and adapts the volume properties to match the appearance for the given perspectives. Additionally, we describe how we can optimize for the environmental lighting to match a desired scene appearance, while keeping volume properties constant. Finally, both techniques can be combined. We demonstrate several use cases of our approach and illustrate its effectiveness.

International audience; Volumetric phenomena are an integral part of standard rendering, yet, no suitable tools to edit characteristic properties are available so far. Either simulation results are used directly, or modifications are high-level, e.g., noise functions to influence appearance. Intuitive artistic control is not possible. We propose a solution to stylize single-scattering volumetric effects. Emission, scattering and extinction become amenable to artistic control while preserving a smooth and coherent appearance when changing the viewpoint. Our approach lets the user define a number of target views to be matched when observing the volume from this perspective. Via an analysis of the volumetric rendering equation, we can show how to link this problem to tomographic reconstruction.

International audience; We propose a non-permanent add-on that enables plenoptic imaging with standard cameras. Our design is based on a physical copying mechanism that multiplies a sensor image into a number of identical copies that still carry the plenoptic information of interest. Via different optical filters, we can then recover the desired information. A minor modification of the design also allows for aperture subsampling and, hence, light-field imaging. As the filters in our design are exchangeable, a reconfiguration for different imaging purposes is possible. We show in a prototype setup that high dynamic range, multispectral, polarization, and light-field imaging can be achieved with our design.

It is both a technical and an artistic challenge to depict three-dimensional content using stereo equipment and a flat two-dimensional screen. On the one hand, the content needs to fit within the limits of a given display technology and at the same time achieve a comfortable viewing experience. Given the technological advances of 3D equipment, especially the latter increases in importance. Modifications to stereo content become necessary that aim at flattening or even removing binocular disparity to adjust the 3D content to match the comfort zone in which the clash between accommodation and vergence stays acceptable. However, applying such modifications can lead to a reduction of crucial depth details. One promising direction is backwardcompatible stereo, for which the disparity is low enough that overlaid stereo pairs seem almost identical. It builds upon the Craik-O'Brien-Cornsweet effect, a visual illusion, which uses so-called Cornsweet profiles to produce a local contrast that leads to a perceived brightness increase. Similarly, Cornsweet profiles in disparity can lead to an illusion of depth. Applying them skilfully at depth discontinuities allows for a reduction of the overall disparity range to ensure a comfortable yet convincing stereo experience. The present work extends the previous idea by showing that Cornsweet profiles can also be used to enhance the 3D impression. This operation can help in regions where the disparity range was compressed, but also to emphasize parts of a scene. A user study measures the performance of backward-compatible stereo and our disparity enhancement.

Retargeting refers to the process by which an image or video is adapted from the display device for which it was meant (target display) to another one (retarget display). The retarget display has different features from the target one such as dynamic range, discretization levels, color gamut, multi-view, and refresh rate spatial resolution. This is a very relevant topic in graphics, given the increasing number of display devices from large, high-contrast screens to small cell phones with limited dynamic range; a lot of techniques are being published in different venues, and it's hard to keep up. For most cases retargeting can be an ill-posed problem, for example in the process of displaying Low Dynamic Range (LDR) or 8-bit content on High Dynamic Range (HDR) displays. Such a problem requires the retargeting algorithm to generate new content which is missing in the input image/frame. In this course, we will present the latest solutions and techniques for retargeting images along various dimensions such as dynamic range, colors, temporal and spatial resolutions, and for the first time offer a much-needed holistic view of the field. Moreover, we are going to show how to measure and analyze the changes applied to an image or video in terms of quality using both psychophysical experiments (subjective) and computational metrics (objective). The course should be of interest to anyone involved in graphics in a broader sense, given the almost unavoidable need to retarget results to different devices -from developers interested in implementing retargeting techniques, to users that just need an overall perspective. For researchers fully engaged in developing multi-dimensional retargeting techniques, this course will serve as a solid background for future algorithms.

Special issue: Proceedings of Pacific Graphics - Session: Lighting & Rendering; International audience; Indirect illumination is an important element for realistic image synthesis, but its computation is expensive and highly dependent on the complexity of the scene and of the BRDF of the involved surfaces. While off-line computation and pre-baking can be acceptable for some cases, many applications (games, simulators, etc.) require real-time or interactive approaches to evaluate indirect illumination. We present a novel algorithm to compute indirect lighting in real-time that avoids costly precomputation steps and is not restricted to low-frequency illumination. It is based on a hierarchical voxel octree representation generated and updated on the fly from a regular scene mesh coupled with an approximate voxel cone tracing that allows for a fast estimation of the visibility and incoming energy. Our approach can manage two light bounces for both Lambertian and glossy materials at interactive framerates (25-70FPS). It exhibits an almost scene-independent performance and can handle complex scenes with dynamic content thanks to an interactive octree-voxelization scheme. In addition, we demonstrate that our voxel cone tracing can be used to efficiently estimate Ambient Occlusion.

We describe a method to parameterize lines generated from animated 3D models in the context of animated line drawings. Cartoons and mechanical illustrations are popular subjects of non-photorealistic drawings and are often generated from 3D models. Adding texture to the lines, for instance to depict brush strokes or dashed lines, enables greater expressiveness, e.g. to distinguish between visible and hidden lines. However, dynamic visibility events and the evolving shape of the lines raise issues that have been only partially explored so far. In this paper, we assume that the entire 3D animation is known ahead of time, as is typically the case for feature animations and off-line rendering. At the core of our method is a geometric formulation of the problem as a parameterization of the space-time surface swept by a 2D line during the animation. First, we build this surface by extracting lines in each frame. We demonstrate our approach with silhouette lines. Then, we locate visibility events that would create discontinuities and propagate them through time. They decompose the surface into charts with a disc topology. We parameterize each chart via a least-squares approach that reflects the specific requirements of line drawing. This step results in a texture atlas of the space-time surface which defines the parameterization for each line. We show that by adjusting a few weights in the least-squares energy, the artist can obtain an artifact-free animated motion in a variety of typical non-photorealistic styles such as painterly strokes and technical line drawing.

Indirect illumination is an important element for realistic image synthesis, but its computation is expensive and highly dependent on the complexity of the scene and of the BRDF of the surfaces involved. While off-line computation and pre-baking can be acceptable for some cases, many applications (games, simulators, etc.) require real-time or interactive approaches to evaluate indirect illumination. We present a novel algorithm to compute indirect lighting in real-time that avoids costly precomputation steps and is not restricted to low frequency illumination. It is based on a hierarchical voxel octree representation generated and updated on-the-fly from a regular scene mesh coupled with an approximate voxel cone tracing that allows a fast estimation of the visibility and incoming energy. Our approach can manage two light bounces for both Lambertian and Glossy materials at interactive framerates (25-70FPS). It exhibits an almost scene-independent performance and allows for fully dynamic content thanks to an interactive octree voxelization scheme. In addition, we demonstrate that our voxel cone tracing can be used to efficiently estimate Ambient Occlusion.

We describe a method to parameterize lines generated from animated 3D models in the context of animated line drawings. Cartoons and mechanical illustrations are popular subjects of non-photorealistic drawings and are often generated from 3D models. Adding texture to the lines, for instance to depict brush strokes or dashed lines, enables greater expressiveness, e.g. to distinguish between visible and hidden lines. However, dynamic visibility events and the evolving shape of the lines raise issues that have been only partially explored so far. In this paper, we assume that the entire 3D animation is known ahead of time, as is typically the case for feature animations and off-line rendering. At the core of our method is a geometric formulation of the problem as a parameterization of the space-time surface swept by a 2D line during the animation. First, we build this surface by extracting lines in each frame. We demonstrate our approach with silhouette lines. Then, we locate visibility events that would create discontinuities and propagate them through time. They decompose the surface into charts with a disc topology. We parameterize each chart via a least-squares approach that reflects the specific requirements of line drawing. This step results in a texture atlas of the space-time surface which defines the parameterization for each line. We show that by adjusting a few weights in the least-squares energy, the artist can obtain an artifact-free animated motion in a variety of typical non-photorealistic styles such as painterly strokes and technical line drawing.

Binocular disparity is an important cue for the human visual system to recognize spatial layout, both in reality and simulated virtual worlds. This paper introduces a perceptual model of disparity for computer graphics that is used to define a metric to compare a stereo image to an alternative stereo image and to estimate the magnitude of the perceived disparity change. Our model can be used to assess the effect of disparity to control the level of undesirable distortions or enhancements (introduced on purpose). A number of psycho-visual experiments are conducted to quantify the mutual effect of disparity magnitude and frequency to derive the model. Besides difference prediction, other applications include compression, and re-targeting. We also present novel applications in form of hybrid stereo images and backward-compatible stereo. The latter minimizes disparity in order to convey a stereo impression if special equipment is used but produces images that appear almost ordinary to the naked eye. The validity of our model and difference metric is again confirmed in a study.

Lens flare is caused by light passing through a photographic lens system in an unintended way. Often considered a degrading artifact, it has become a crucial component for realistic imagery and an artistic means that can even lead to an increased perceived brightness. So far, only costly offline processes allowed for convincing simulations of the complex light interactions. In this paper, we present a novel method to interactively compute physically-plausible flare renderings for photographic lenses. The underlying model covers many components that are important for realism, such as imperfections, chromatic and geometric lens aberrations, and antireflective lens coatings. Various acceleration strategies allow for a performance/quality tradeoff, making our technique applicable both in real-time applications and in high-quality production rendering. We further outline artistic extensions to our system.