Abstract We present a technique for real‐time adjustment of spatial frequencies in images and videos. Our method allows for both decreasing and increasing of frequencies, and is orthogonal to image resizing. Thus, it can be used to automatically adjust spatial frequencies to preserve the appearance of structured patterns during image downscaling and upscaling. By pre‐computing the image's space‐frequency decomposition and its unwrapped phases, these operations can be performed in real time, thanks to our novel mathematical perspective on frequency manipulation of digital images: interpreting the problem through the theory of instantaneous frequencies and phase unwrapping. To make this possible, we introduce an algorithm for the simultaneous phase unwrapping of several unordered frequency components, which also deals with the frequency‐sign ambiguity of real signals. As such, our method provides theoretical and practical improvements to the concept of spectral remapping, enabling real‐time performance and improved color handling. We demonstrate its effectiveness on a large number of images subject to frequency adjustment. By providing real‐time control over the spatial frequencies associated with structured patterns, our technique expands the range of creative and technical possibilities for image and video processing.

We introduce a technique to synthetically increase the framerate of semi-repetitive videos (i.e., videos of motion that repeats but not in an identical fashion) to aid in visualization. By reordering and combining frames from all repetitions, we produce a single non-repetitive sequence with much higher temporal resolution. Then, we use a novel frame warping technique based on a dense corrective flow to counteract differences between repetitions. The resulting video maintains smoothness of motion and additionally allows for seamless, infinite looping. We demonstrate the effectiveness of the proposed solution both quantitatively, by measuring the improvement over existing methods, and qualitatively, by performing a user evaluation and providing several examples in the article and accompanying video.

We present a technique for synthesizing realistic noise for digital photographs. It can adjust the noise level of an input photograph, either increasing or decreasing it, to match a target ISO level. Our solution learns the mappings among different ISO levels from unpaired data using generative adversarial networks. We demonstrate its effectiveness both quantitatively, using Kullback-Leibler divergence and Kolmogorov-Smirnov test, and qualitatively through a large number of examples. We also demonstrate its practical applicability by using its results to significantly improve the performance of a state-of-the-art trainable denoising method. Our technique should benefit several computer-vision applications that seek robustness to noisy scenarios.

Abstract In this paper we use a simplified model of the human visual system to explain why humans tend do prefer “sharpened” digital images. From this model we then derive a family of image prefilters specifically adapted to viewing conditions and user preference, allowing for the trade‐off between ringing and aliasing while maximizing image sharpness. We discuss how our filters can be applied in a variety of situations ranging from Monte Carlo rendering to image downscaling, and we show how they consistently give sharper results while having an efficient implementation and ease of use (there are no free parameters that require manual tuning). We demonstrate the effectiveness of our simple sharp prefilters through a user study that indicates a clear preference to our approach compared to the state‐of‐the‐art.

Abstract Despite considerable advances in natural image matting over the last decades, video matting still remains a difficult problem. The main challenges faced by existing methods are the large amount of user input required, and temporal inconsistencies in mattes between pairs of adjacent frames. We present a temporally‐coherent matte‐propagation method for videos based on PatchMatch and edge‐aware filtering. Given an input video and trimaps for a few frames, including the first and last, our approach generates alpha mattes for all frames of the video sequence. We also present a user scribble‐based interface for video matting that takes advantage of the efficiency of our method to interactively refine the matte results. We demonstrate the effectiveness of our approach by using it to generate temporally‐coherent mattes for several natural video sequences. We perform quantitative comparisons against the state‐of‐the‐art sparse‐input video matting techniques and show that our method produces significantly better results according to three different metrics. We also perform qualitative comparisons against the state‐of‐the‐art dense‐input video matting techniques and show that our approach produces similar quality results while requiring only about 7% of the amount of user input required by such techniques. These results show that our method is both effective and user‐friendly, outperforming state‐of‐the‐art solutions.

Abstract We present a convolutional neural network architecture for performing joint design of color filter array (CFA) patterns and demosaicing. Our generic model allows the training of CFAs of arbitrary sizes, optimizing each color filter over the entire RGB color space. The patterns and algorithms produced by our method provide high‐quality color reconstructions. We demonstrate the effectiveness of our approach by showing that its results achieve higher PSNR than the ones obtained with state‐of‐the‐art techniques on all standard demosaicing datasets, both for noise‐free and noisy scenarios. Our method can also be used to obtain demosaicing strategies for pre‐defined CFAs, such as the Bayer pattern, for which our results also surpass even the demosaicing algorithms specifically designed for such a pattern.

We present an image downscaling technique capable of appropriately representing high-frequency structured patterns. Our method breaks conventional wisdom in sampling theory---instead of discarding high-frequency information to avoid aliasing, it controls aliasing by remapping such information to the representable range of the downsampled spectrum. The resulting images provide more faithful representations of their original counterparts, retaining visually-important details that would otherwise be lost. Our technique can be used with any resampling method and works for both natural and synthetic images. We demonstrate its effectiveness on a large number of images downscaled in combination with various resampling strategies. By providing an alternative solution for a long-standing problem, our method opens up new possibilities for image processing.

Fluid animation methods based on Eulerian grids have long struggled to resolve flows involving narrow gaps and thin solid features. Past approaches have artificially inflated or voxelized boundaries, although this sacrifices the correct geometry and topology of the fluid domain and prevents flow through narrow regions. We present a boundary-respecting fluid simulator that overcomes these challenges. Our solution is to intersect the solid boundary geometry with the cells of a background regular grid to generate a topologically correct, boundary-conforming cut-cell mesh. We extend both pressure projection and velocity advection to support this enhanced grid structure. For pressure projection, we introduce a general graph-based scheme that properly preserves discrete incompressibility even in thin and topologically complex flow regions, while nevertheless yielding symmetric positive definite linear systems. For advection, we exploit polyhedral interpolation to improve the degree to which the flow conforms to irregular and possibly non-convex cell boundaries, and propose a modified PIC/FLIP advection scheme to eliminate the need to inaccurately reinitialize invalid cells that are swept over by moving boundaries. The method naturally extends the standard Eulerian fluid simulation framework, and while we focus on thin boundaries, our contributions are beneficial for volumetric solids as well. Our results demonstrate successful one-way fluid-solid coupling in the presence of thin objects and narrow flow regions even on very coarse grids.

Abstract We present a discrete‐time mathematical formulation for applying recursive digital filters to non‐uniformly sampled signals. Our solution presents several desirable features: it preserves the stability of the original filters; is well‐conditioned for low‐pass, high‐pass, and band‐pass filters alike; its cost is linear in the number of samples and is not affected by the size of the filter support. Our method is general and works with any non‐uniformly sampled signal and any recursive digital filter defined by a difference equation. Since our formulation directly uses the filter coefficients, it works out‐of‐the‐box with existing methodologies for digital filter design. We demonstrate the effectiveness of our approach by filtering non‐uniformly sampled signals in various image and video processing tasks including edge‐preserving color filtering, noise reduction, stylization, and detail enhancement. Our formulation enables, for the first time, edge‐aware evaluation of any recursive infinite impulse response digital filter (not only low‐pass), producing high‐quality filtering results in real time.

We describe a technique to generate imagery with improved sharpness for individuals having refractive vision problems. Our method can reduce their dependence on corrective eyewear. It also benefits individuals with normal vision by improving visual acuity at a distance and of small details. Our approach does not require custom hardware. Instead, the calculated images can be shown on a standard computer display, on printed paper, or superimposed on a physical scene using a projector. Our technique uses a constrained total variation method to produce a deconvolution result which, upon observation, appears sharp at the edges. We introduce a novel relative total variation term that enables controlling ringing reduction, contrast gain, and sharpness. The end result is the ability to generate sharper appearing images, even for individuals with refractive vision problems including myopia, hyperopia, presbyopia, and astigmatism. Our approach has been validated in simulation, in camera-screen experiments, and in a study with human observers.

Abstract We present an efficient approach for performing smoke simulation on curvilinear grids. Our technique is based on a fast unconditionally‐stable advection algorithm and on a new and efficient solution to enforce mass conservation. It uses a staggered‐grid variable arrangement, and has linear cost on the number of grid cells. Our method naturally integrates itself with overlapping‐grid techniques, lending to an efficient way of producing highly‐realistic animations of dynamic scenes. Compared to approaches based on regular grids traditionally used in computer graphics, our method allows for better representation of boundary conditions, with just a small increment in computational cost. Thus, it can be used to evaluate aerodynamic properties, possibly enabling unexplored applications in computer graphics, such as interactive computation of lifting forces on complex objects. We demonstrate the effectiveness of our approach, both in 2‐D and 3‐D, through a variety of high‐quality smoke animations.

Color is one of the most common ways to convey information in visualization applications. Color vision deficiency (CVD) affects approximately 200 million individuals worldwide and considerably degrades their performance in understanding such contents by creating red-green or blue-yellow ambiguities. While several content-specific methods have been proposed to resolve these ambiguities, they cannot achieve this effectively in many situations for contents with a large variety of colors. More importantly, they cannot facilitate color identification. We propose a technique for using patterns to encode color information for individuals with CVD, in particular for dichromats. We present the first content-independent method to overlay patterns on colored visualization contents that not only minimizes ambiguities but also allows color identification. Further, since overlaying patterns does not compromise the underlying original colors, it does not hamper the perception of normal trichromats. We validated our method with two user studies: one including 11 subjects with CVD and 19 normal trichromats, and focused on images that use colors to represent multiple categories; and another one including 16 subjects with CVD and 22 normal trichromats, which considered a broader set of images. Our results show that overlaying patterns significantly improves the performance of dichromats in several color-based visualization tasks, making their performance almost similar to normal trichromats'. More interestingly, the patterns augment color information in a positive manner, allowing normal trichromats to perform with greater accuracy.

Abstract We present a coded‐aperture method based on a family of masks obtained as the convolution of one “hole” with a structural component consisting of an arrangement of Dirac delta functions. We call the arrangement of delta functions the structural component of the mask, and use it to efficiently encode scene distance information. We illustrate the potential of our approach by analyzing a family of masks defined by a circular hole component and a structural component consisting of a linear combination of three Dirac deltas. We show that the structural component transitions from well conditioned to ill conditioned as the relative weight of the central peak varies with respect to the lateral ones. For the well‐conditioned structural components, deconvolution is efficiently performed by inverse filtering, allowing for fast estimation of scene depth. We demonstrate the effectiveness of our approach by constructing a mask for distance coding and using it to recover pairs of distance maps and structurally‐deconvolved images from single photographs. For this application, we obtain significant speedup, and extended range and depth resolution compared to previous techniques.

We present a technique for performing high-dimensional filtering of images and videos in real time. Our approach produces high-quality results and accelerates filtering by computing the filter's response at a reduced set of sampling points, and using these for interpolation at allNinput pixels. We show that for a proper choice of these sampling points, the total cost of the filtering operation is linear both inNand in the dimensiondof the space in which the filter operates. As such, ours is the first high-dimensional filter with such a complexity. We present formal derivations for the equations that define our filter, as well as for an algorithm to compute the sampling points. This provides a sound theoretical justification for our method and for its properties. The resulting filter is quite flexible, being capable of producing responses that approximate either standard Gaussian, bilateral, or non-local-means filters. Such flexibility also allows us to demonstrate the first hybrid Euclidean-geodesic filter that runs in a single pass. Our filter is faster and requires less memory than previous approaches, being able to process a 10-Megapixel full-color image at 50 fps on modern GPUs. We illustrate the effectiveness of our approach by performing a variety of tasks ranging from edge-aware color filtering in 5-D, noise reduction (using up to 147 dimensions), single-pass hybrid Euclidean-geodesic filtering, and detail enhancement, among others.

We introduce tailored displays that enhance visual acuity by decomposing virtual objects and placing the resulting anisotropic pieces into the subject's focal range. The goal is to free the viewer from needing wearable optical corrections when looking at displays. Our tailoring process uses aberration and scattering maps to account for refractive errors and cataracts. It splits an object's light field into multiple instances that are each in-focus for a given eye sub-aperture. Their integration onto the retina leads to a quality improvement of perceived images when observing the display with naked eyes. The use of multiple depths to render each point of focus on the retina creates multi-focus, multi-depth displays. User evaluations and validation with modified camera optics are performed. We propose tailored displays for daily tasks where using eyeglasses are unfeasible or inconvenient (e.g., on head-mounted displays, e-readers, as well as for games); when a multi-focus function is required but undoable (e.g., driving for farsighted individuals, checking a portable device while doing physical activities); or for correcting the visual distortions produced by high-order aberrations that eyeglasses are not able to.

We present a new approach for performing high-quality edge-preserving filtering of images and videos in real time. Our solution is based on a transform that defines an isometry between curves on the 2D image manifold in 5D and the real line. This transform preserves the geodesic distance between points on these curves, adaptively warping the input signal so that 1D edge-preserving filtering can be efficiently performed in linear time. We demonstrate three realizations of 1D edge-preserving filters, show how to produce high-quality 2D edge-preserving filters by iterating 1D-filtering operations, and empirically analyze the convergence of this process. Our approach has several desirable features: the use of 1D operations leads to considerable speedups over existing techniques and potential memory savings; its computational cost is not affected by the choice of the filter parameters; and it is the first edge-preserving filter to work on color images at arbitrary scales in real time, without resorting to subsampling or quantization. We demonstrate the versatility of our domain transform and edge-preserving filters on several real-time image and video processing tasks including edge-preserving filtering, depth-of-field effects, stylization, recoloring, colorization, detail enhancement, and tone mapping.

We introduce an interactive method to assess cataracts in the human eye by crafting an optical solution that measures the perceptual impact of forward scattering on the foveal region. Current solutions rely on highly-trained clinicians to check the back scattering in the crystallin lens and test their predictions on visual acuity tests. Close-range parallax barriers create collimated beams of light to scan through sub-apertures, scattering light as it strikes a cataract. User feedback generates maps for opacity, attenuation, contrast and sub-aperture point-spread functions. The goal is to allow a general audience to operate a portable high-contrast light-field display to gain a meaningful understanding of their own visual conditions. User evaluations and validation with modified camera optics are performed. Compiled data is used to reconstruct the individual's cataract-affected view, offering a novel approach for capturing information for screening, diagnostic, and clinical analysis.

THIS IEEE Transactions on Visualization and Computer Graphics (TVCG) special section brings to you extended versions of four excellent articles originally presented at the Symposium on Interactive 3D Graphics and Games (I3D) in 2010. Since 1986, I3D has been a venue for cutting-edge computer science research in interactive graphics and human interaction. The field has grown significantly since the founding of I3D, but the symposium has maintained its premier status. Today, I3D is known for the close integration of academia and industry, and such is clear from the mixture of attendees and from the mixture of authors of the articles in this section. The symposium itself is also very popular, for it provides a great venue for meeting fellow researchers, forming new collaborations, and brainstorming new solutions. I3D 2010 received 71 submissions from 19 countries in four continents. Each paper received at least three independent reviews by a group of 86 experts in the field of computer graphics and interactive techniques. After a discussion phase, 23 papers were selected for publication and presentation at the symposium (an acceptance rate of 32 percent). There have been no limits imposed on the number of accepted papers, and the decisions were based purely on the submissions’ merits. Following a tradition started with I3D 2009, we invited the authors of four of the accepted papers to expand their work with new insights and results for publication in this special section of TVCG on I3D. The choice of the invited papers was based on the evaluation and comments of our expert reviewers. These papers went through a complete journal review process, which included multiple iterations of editing and review. “Stochastic Transparency” by Eric Enderton, Erik Sintorn, Peter Shirley, and David Luebke addresses the problem of achieving order-independent transparency for interactive rendering. The solution provided by the authors presents several desirable features: the required memory does not depend on the scene’s depth complexity; it renders a fixed number of passes, with its running time growing linearly with the number of fragments; it is general in the sense that it can replace multiple transparency algorithms for different scenarios; it is also easy to implement, and is a good fit to modern, massively parallel GPUs. The technique provides a practical solution for interactive applications, being capable of rendering all kinds of transparent geometry, and providing a unifying approach for orderindependent transparency, anti-aliasing, and shadowing. “Efficient Sparse Voxel Octrees” by Samuli Laine and Tero Karras explores the use of voxel representations for rendering complex detailed geometry on current and future GPUs. In order to efficiently ray cast the resulting models, the authors propose a compact data structure for storing voxels. In this representation, voxels are augmented with contour information to increase geometry resolution. The paper also describes a new normal compression format for storing high-precision object-space normals. Using the proposed infrastructure, the authors challenge the current graphics trend of using a base mesh augmented with fine details represented by textures and displacement maps: as the amount of color and geometric detail information grows beyond a certain limit, wouldn’t it make more sense to use a voxel representation to store both geometry and its associated attributes? “Frankenrigs: Building Character Rigs from Multiple Sources” by Christian Miller, Okan Arikan, and Don Fussel addresses an important practical problem in 3D character animation. Rigging and skinning a character is a fundamental animation task, but a time-consuming and tedious one even for experts. The authors present an automatic solution for generating good quality rigging and skinning that can greatly simplify the work of animators. Given a character’s 3D mesh with annotated joints, the technique finds good matches for individual parts of the model by scanning a database of partial rigs. By transferring information from the partial rigs to the target mesh, the approach produces a skeleton and skinning weights whose quality are similar to the ones produced by expert animators. “Improving Shape Depiction under Arbitrary Rendering” by Romain Vergne, Romain Pacanowski, Pascal Barla, Xavier Granier, and Christophe Schlick introduces a technique for enhancing shape depiction by scaling the reflected light as a function of curvature and material properties. Their solution can be used with any kind of material and works with both direct and global illumination. It can also be used with different lighting environments, supports inter-reflections, and works in real time. By providing intuitive control over the resulting shading, this 1034 IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS, VOL. 17, NO. 8, AUGUST 2011

Abstract Image matting aims at extracting foreground elements from an image by means of color and opacity (alpha) estimation. While a lot of progress has been made in recent years on improving the accuracy of matting techniques, one common problem persisted: the low speed of matte computation. We present the first real‐time matting technique for natural images and videos. Our technique is based on the observation that, for small neighborhoods, pixels tend to share similar attributes. Therefore, independently treating each pixel in the unknown regions of a trimap results in a lot of redundant work. We show how this computation can be significantly and safely reduced by means of a careful selection of pairs of background and foreground samples. Our technique achieves speedups of up to two orders of magnitude compared to previous ones, while producing high‐quality alpha mattes. The quality of our results has been verified through an independent benchmark. The speed of our technique enables, for the first time, real‐time alpha matting of videos, and has the potential to enable a new class of exciting applications.

Abstract We present an automatic image‐recoloring technique for enhancing color contrast for dichromats whose computational cost varies linearly with the number of input pixels. Our approach can be efficiently implemented on GPUs, and we show that for typical image sizes it is up to two orders of magnitude faster than the current state‐of‐the‐art technique. Unlike previous approaches, ours preserve temporal coherence and, therefore, is suitable for video recoloring. We demonstrate the effectiveness of our technique by integrating it into a visualization system and showing, for the first time, real‐time high‐quality recolored visualizations for dichromats.

We introduce an interactive, portable, and inexpensive solution for estimating refractive errors in the human eye. While expensive optical devices for automatic estimation of refractive correction exist, our goal is to greatly simplify the mechanism by putting the human subject in the loop. Our solution is based on a high-resolution programmable display and combines inexpensive optical elements, interactive GUI, and computational reconstruction. The key idea is to interface a lenticular view-dependent display with the human eye in close range - a few millimeters apart. Via this platform, we create a new range of interactivity that is extremely sensitive to parameters of the human eye, like refractive errors, focal range, focusing speed, lens opacity, etc. We propose several simple optical setups, verify their accuracy, precision, and validate them in a user study.

In the above titled paper (ibid., vol. 15, no. 6, pp. 1291-1298, Nov./Dec. 09), there were typos in equations (17) and (18). The correct versions are presented here.

We introduce a physiologically-based model for pupil light reflex (PLR) and an image-based model for iridal pattern deformation. Our PLR model expresses the pupil diameter as a function of the lighting of the environment, and is described by a delay-differential equation, naturally adapting the pupil diameter even to abrupt changes in light conditions. Since the parameters of our PLR model were derived from measured data, it correctly simulates the actual behavior of the human pupil. Another contribution of our work is a model for realistic deformation of the iris pattern as a function of pupil dilation and constriction. Our models produce high-fidelity appearance effects and can be used to produce real-time predictive animations of the pupil and iris under variable lighting conditions. We assess the predictability and quality of our simulations through comparisons of modeled results against measured data derived from experiments also described in this work. Combined, our models can bring facial animation to new photorealistic standards.

Color vision deficiency (CVD) affects approximately 200 million people worldwide, compromising the ability of these individuals to effectively perform color and visualization-related tasks. This has a significant impact on their private and professional lives. We present a physiologically-based model for simulating color vision. Our model is based on the stage theory of human color vision and is derived from data reported in electrophysiological studies. It is the first model to consistently handle normal color vision, anomalous trichromacy, and dichromacy in a unified way. We have validated the proposed model through an experimental evaluation involving groups of color vision deficient individuals and normal color vision ones. Our model can provide insights and feedback on how to improve visualization experiences for individuals with CVD. It also provides a framework for testing hypotheses about some aspects of the retinal photoreceptors in color vision deficient individuals.

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We present an efficient and automatic image-recoloring technique for dichromats that highlights important visual details that would otherwise be unnoticed by these individuals. While previous techniques approach this problem by potentially changing all colors of the original image, causing their results to look unnatural to color vision deficients, our approach preserves, as much as possible, the image's original colors. Our approach is about three orders of magnitude faster than previous ones. The results of a paired-comparison evaluation carried out with fourteen color-vision deficients (CVDs) indicated the preference of our technique over the state-of-the-art automatic recoloring technique for dichromats. When considering information visualization examples, the subjects tend to prefer our results over the original images. An extension of our technique that exaggerates color contrast tends to be preferred when CVDs compared pairs of scientific visualization images. These results provide valuable information for guiding the design of visualizations for color-vision deficients.

Light refraction is an important optical phenomenon whose simulation greatly contributes to the realism of synthesized images. Although ray tracing can correctly simulate light refraction, doing it in real time still remains a challenge. This work presents an image-space technique to simulate the refraction of distant environments in real time. Contrary to previous approaches for interactive refraction at multiple interfaces, the proposed technique does not require any preprocessing. As a result, it can be directly applied to objects undergoing shape deformations, which is a common and important feature for character animation in computer games and movies. Our approach is general in the sense that it can be used with any object representation that can be rasterized on a programmable GPU. It is based on an efficient ray-intersection procedure performed against a dynamic depth map and carried out in 2D texture space. We demonstrate the effectiveness of our approach by simulating refractions through animated characters composed of several hundred thousand polygons in real time.

The ability to represent non-height-field mesostructure details is of great importance for rendering complex surface patterns, such as weave and multilayer structures. Currently, such representations are based on the use of 3D textures or large datasets of sampled data. While some of the 3D-texture-based approaches can achieve interactive performance, all these approaches require large amounts of memory. We present a technique for mapping non-height-field structures onto arbitrary polygonal models in real time, which has low memory requirements. It generalizes the notion of relief mapping to support multiple layers. This technique can be used to render realistic impostors of 3D objects that can be viewed from close proximity and from a wide angular range. Contrary to traditional impostors, these new one-polygon representations can be observed from both sides, producing correct parallax and views that are consistent with the observation of the 3D geometry they represent.

We introduce the notion of oriented charges to compute distance fields from unorganized point clouds. Unlike traditional implicit function methods that usually require normal information, our approach only uses information about the position of the samples. Our approach is adaptive, using an octree to reorganize the input points, thus avoiding difficulties often associated with the use of local distance fields. The resulting representation is simple, efficient and general in the sense that it handles complex models of arbitrary topology, is robust in the presence of noise and fills holes automatically.

This paper presents a technique for mapping relief textures onto arbitrary polygonal models in real time. In this approach, the mapping of the relief data is done in tangent space. As a result, it can be applied to polygonal representations of curved surfaces producing correct self-occlusions, interpenetrations, shadows and per-pixel lighting effects. The approach can be used to consistently add surface details to geometric models undergoing deformations, such as in the case of animated characters commonly found in games. The technique uses an inverse formulation (i.e., pixel driven) based on an efficient ray-height-field intersection algorithm implemented on the GPU. It supports extreme close-up views of the surfaces, mip mapping and anisotropic texture filtering. Also, contrary to high-dimensional representations of surface details, the low memory requirements of the proposed technique do not restrict its use to tiled textures.

This paper presents a novel approach for surface reconstruction from point clouds. The proposed technique is general in the sense that it naturally handles both manifold and non-manifold surfaces, providing a consistent way for reconstructing closed surfaces as well as surfaces with boundaries. It is also robust in the presence of noise, irregular sampling and surface gaps. Furthermore, it is fast, parallelizable and easy to implement because it is based on simple local operations. In this approach, surface reconstruction consists of three major steps: first, the space containing the point cloud is subdivided, creating a voxel representation. Then, a voxel surface is computed using gap filling and topological thinning operations. Finally, the resulting voxel surface is converted into a polygonal mesh. We demonstrate the effectiveness of our approach by reconstructing polygonal models from range scans of real objects as well as from synthetic data.

We present a technique for mapping relief textures onto arbitrary polygonal models in real time, producing correct self-occlusions, interpenetrations, shadows and per-pixel lighting. The technique uses a pixel-driven formulation based on an efficient ray-height-field intersection implemented on the GPU. It has very low memory requirements, supports extreme close-up views of the surfaces and can be applicable to surfaces undergoing deformation.

The Internet, as an accessible network with global connectivity, presents itself as the likely solution for the supporting infrastructure of cyberspace. In contrast, the field of virtual environments (VE) is fragmented with a wide proliferation of different systems, as a result of the current development trend. However, these divergent systems present a significant overlap of functionality that represents a waste of development resources and a detriment to innovation. This paper proposes Mayhem as a new approach to the design and development of VE systems. Our approach relies heavily on component design methodology coupled with a simple layered approach to system architectures. The combination of the two promotes the construction of systems from smaller building blocks, which may have been developed by different sources, each specializing in the supported functionality. Although Mayhem promotes the trend of middleware, it requires a common base infrastructure - the Java Adaptive Dynamic Environment (JADE). To demonstrate how to build a VE system using Mayhem, the paper describes a simple prototype of a VE and some of its key building blocks.

We describe the construction of a lightweight, point-and-shoot 3D color camera, intended for reconstruction of smooth surfaces. Our approach extracts 3D shape from a single image and is completely automatic. The 3D camera consists of an eye-safe laser pattern generator attached to a consumer-grade digital camera and some image processing software.

The modeling of real scenes is a complex and challenging task for which the use of laser rangefinders is one of the most promising approaches. Unfortunately, in many situations, it is not possible or practical to guarantee appropriate sampling of all surfaces in the scene. For example, occlusions and accessibility limitations to certain regions of the scene may cause some areas not to be visible by the scanner, resulting in incomplete or incorrectly reconstructed models. This paper describes a pipeline and a system implementation for improving model reconstruction from incomplete information available from range images. Categories and Subject Descriptors (according to ACM CCS): I.3.7 [Computer Graphics]: Three-Dimensional Graphics and Realism, Virtual Reality

Most rendering engines subdivide arbitrary polygons into a collection of triangles, which are then rendered independently of each other. This procedure can introduce severe artifacts when rendering texture-mapped quadrilaterals. These errors result from a fundamental limitation: the impossibility of performing general projective mappings using only the information available at the vertices of a single triangle. Texture mapping involving arbitrary quadrilaterals has practical importance in applications that use real images as textures, such as in image-based modeling and rendering. The paper presents an efficient adaptive-subdivision solution to the problem, which, due to its simplicity, can be easily incorporated into graphics APIs.

We present an extension to texture mapping that supports the representation of 3-D surface details and view motion parallax. The results are correct for viewpoints that are static or moving, far away or nearby. Our approach is very simple: a relief texture (texture extended with an orthogonal displacement per texel) is mapped onto a polygon using a two-step process: First, it is converted into an ordinary texture using a surprisingly simple 1-D forward transform. The resulting texture is then mapped onto the polygon using standard texture mapping. The 1-D warping functions work in texture coordinates to handle the parallax and visibility changes that result from the 3-D shape of the displacement surface. The subsequent texture-mapping operation handles the transformation from texture to screen coordinates.

We present a compact, image-based representation for threedimensional objects with complex shapes that can be rendered with correct perspective from arbitrary viewpoints using a listpriority algorithm. Objects are represented by six layered depth images sharing a single center of projection. They can be scaled, and freely translated and rotated, being used as primitives to construct more complex scenes. We also present a new listpriority algorithm for rendering such scenes and a back face culling strategy for a class of image-based objects. We demonstrate these concepts by constructing image-based representations from both synthetic and real objects, and rendering them at interactive rates on a PC. Due to their minimum storage requirements and rendering simplicity, image-based objects can find potential uses in games, virtual museum applications, and web catalogs. CR Categories and Subject Descriptors: I.3.3 [Computer Graphics]: Picture/Image Generation -- Display Algorithms; I.3.7 [...

This paper presents efficient image-based rendering techniques used in the context of an architectural walkthrough system. Portals (doors and windows) are rendered by warping layered depth images (LDIs). In a preprocessing phase, for every portal, a number of pre-rendered images are combined into an LDI. The resulting LDI stores, exactly once, all surfaces visible in at least one of the images used in the construction, so most of the exposure errors are efficiently eliminated. The LDI can be warped in the McMillan occlusion compatible ordering. A substantial increase in performance is obtained by warping in parallel. Our parallelization scheme achieves good load balancing, scales with the number of processors, and preserves the occlusion compatible ordering. A fast, conservative reference-image-space clipping algorithm also reduces the warping effort.