DSpace Repository :: Browsing Full Papers 2008 - CGF 27-Issue 2 by Issue Date (2024)

In this paper we propose a novel method for detecting and removing shadows from a single image thereby obtaining a high-quality shadow-free image. With minimal user assistance, we first identify shadowed and lit areas on the same surface in the scene using an illumination-invariant distance measure. These areas are used to estimate the parameters of an affine shadow formation model. A novel pyramid-based restoration process is then applied to produce a shadow-free image, while avoiding loss of texture contrast and introduction of noise. Unlike previous approaches, we account for varying shadow intensity inside the shadowed region by processing it from the interior towards the boundaries. Finally, to ensure a seamless transition between the original and the recovered regions we apply image inpainting along a thin border. We demonstrate that our approach produces results that are in most cases superior in quality to those of previous shadow removal methods. We also show that it is possible to easily composite the extracted shadow onto a new background or modify its size and direction in the original image.

We propose a method for rendering volumetric data sets at interactive frame rates while supporting dynamic ambient occlusion as well as an approximation to color bleeding. In contrast to ambient occlusion approaches for polygonal data, techniques for volumetric data sets have to face additional challenges, since by changing rendering parameters, such as the transfer function or the thresholding, the structure of the data set and thus the light interactions may vary drastically. Therefore, during a preprocessing step which is independent of the rendering parameters we capture light interactions for all combinations of structures extractable from a volumetric data set. In order to compute the light interactions between the different structures, we combine this preprocessed information during rendering based on the rendering parameters defined interactively by the user. Thus our method supports interactive exploration of a volumetric data set but still gives the user control over the most important rendering parameters. For instance, if the user alters the transfer function to extract different structures from a volumetric data set the light interactions between the extracted structures are captured in the rendering while still allowing interactive frame rates. Compared to known local illumination models for volume rendering our method does not introduce any substantial rendering overhead and can be integrated easily into existing volume rendering applications. In this paper we will explain our approach, discuss the implications for interactive volume rendering and present the achieved results.

We present a GPU accelerated volume ray casting system interactively driving a multi-user light field display. The display, driven by a single programmable GPU, is based on a specially arranged array of projectors and a holographic screen and provides full horizontal parallax. The characteristics of the display are exploited to develop a specialized volume rendering technique able to provide multiple freely moving naked-eye viewers the illusion of seeing and manipulating virtual volumetric objects floating in the display workspace. In our approach, a GPU ray-caster follows rays generated by a multiple-center-of-projection technique while sampling pre-filtered versions of the dataset at resolutions that match the varying spatial accuracy of the display. The method achieves interactive performance and provides rapid visual understanding of complex volumetric data sets even when using depth oblivious compositing techniques.

Depth and visual hulls are useful for quick reconstruction and rendering of a 3D object based on a number of reference views. However, for many scenes, especially multi-object, these hulls may contain significant artifacts known as phantom geometry. In depth hulls the phantom geometry appears behind the scene objects in regions occluded from all the reference views. In visual hulls the phantom geometry may also appear in front of the objects because there is not enough information to unambiguously imply the object positions.In this work we identify which parts of the depth and visual hull might constitute phantom geometry. We define the notion of reduced depth hull and reduced visual hull as the parts of the corresponding hull that are phantom-free. We analyze the role of the depth information in identification of the phantom geometry. Based on this, we provide an algorithm for rendering the reduced depth hull at interactive frame-rates and suggest an approach for rendering the reduced visual hull. The rendering algorithms take advantage of modern GPU programming techniques.Our techniques bypass explicit reconstruction of the hulls, rendering the reduced depth or visual hull directly from the reference views.

In recent years, a wide range of generalized barycentric coordinates has been suggested. However, all of them lack control over derivatives. We show how the notion of barycentric coordinates can be extended to specify derivatives at control points. This is also known as Hermite interpolation. We introduce a method to modify existing barycentric coordinates to higher order barycentric coordinates and demonstrate, using higher order mean value coordinates, that our method, although conceptually simple and easy to implement, can be used to give easy and intuitive control at interactive frame rates over local space deformations such as rotations.

Recently, it has become increasingly popular to represent animations not by means of a classical skeleton-based model, but in the form of deforming mesh sequences. The reason for this new trend is that novel mesh deformation methods as well as new surface based scene capture techniques offer a great level of flexibility during animation creation. Unfortunately, the resulting scene representation is less compact than skeletal ones and there is not yet a rich toolbox available which enables easy post-processing and modification of mesh animations. To bridge this gap between the mesh-based and the skeletal paradigm, we propose a new method that automatically extracts a plausible kinematic skeleton, skeletal motion parameters, as well as surface skinning weights from arbitrary mesh animations. By this means, deforming mesh sequences can be fully-automatically transformed into fullyrigged virtual subjects. The original input can then be quickly rendered based on the new compact bone and skin representation, and it can be easily modified using the full repertoire of already existing animation tools.

Currently 3D animation rendering and video compression are completely independent processes even if rendered frames are streamed on-the-fly within a client-server platform. In such scenario, which may involve time-varying transmission bandwidths and different display characteristics at the client side, dynamic adjustment of the rendering quality to such requirements can lead to a better use of server resources. In this work, we present a framework where the renderer and MPEG codec are coupled through a straightforward interface that provides precise motion vectors from the rendering side to the codec and perceptual error thresholds for each pixel in the opposite direction. The perceptual error thresholds take into account bandwidth-dependent quantization errors resulting from the lossy com-pression as well as image content-dependent luminance and spatial contrast masking. The availability of the discrete cosine transform (DCT) coefficients at the codec side enables to use advanced models of the human visual system (HVS) in the perceptual error threshold derivation without incurring any significant cost. Those error thresholds are then used to control the rendering quality and make it well aligned with the compressed stream quality. In our prototype system we use the lightcuts technique developed by Walter et al., which we enhance to handle dynamic image sequences, and an MPEG-2 implementation. Our results clearly demonstrate many advantages of coupling the rendering with video compression in terms of faster rendering. Furthermore, temporally coherent rendering leads to a reduction of temporal artifacts.

Human facial gestures often exhibit such natural stochastic variations as how often the eyes blink, how often the eyebrows and the nose twitch, and how the head moves while speaking. The stochastic movements of facial features are key ingredients for generating convincing facial expressions. Although such small variations have been simulated using noise functions in many graphics applications, modulating noise functions to match natural variations induced from the affective states and the personality of characters is difficult and not intuitive. We present a technique for generating subtle expressive facial gestures (facial expressions and head motion) semi-automatically from motion capture data. Our approach is based on Markov random fields that are simulated in two levels. In the lower level, the coordinated movements of facial features are captured, parameterized, and transferred to synthetic faces using basis shapes. The upper level represents independent stochastic behavior of facial features. The experimental results show that our system generates expressive facial gestures synchronized with input speech.

Algebraic Point Set Surfaces (APSS) define a smooth surface from a set of points using local moving least-squares (MLS) fitting of algebraic spheres. In this paper we first revisit the spherical fitting problem and provide a new, more generic solution that includes intuitive parameters for curvature control of the fitted spheres. As a second contribution we present a novel real-time rendering system of such surfaces using a dynamic up-sampling strategy combined with a conventional splatting algorithm for high quality rendering. Our approach also includes a new view dependent geometric error tailored to efficient and adaptive up-sampling of the surface. One of the key features of our system is its high degree of flexibility that enables us to achieve high performance even for highly dynamic data or complex models by exploiting temporal coherence at the primitive level. We also address the issue of efficient spatial search data structures with respect to construction, access and GPU friendliness. Finally, we present an efficient parallel GPU implementation of the algorithms and search structures.

We present a system for creating and manipulating layered procedural surface editing operations, which is motivated by the limited support for iterative design in free-form modeling. A combination of sketch-based and traditional modeling tools are used to design soft displacements, sharp creases, extrusions along 3D paths, and topological holes and handles. Using local parameterizations, these edits are combined in a dynamic hierarchy, enabling procedural operations like linked copy-and-paste and drag-and-drop layer-based editing. Such dynamic, layered surface compositing is formalized as a Surface Tree, an analog of CSG trees which generalizes previous hierarchical surface modeling techniques. By anchoring tree nodes in the parameter space of lower layers, our surface tree implementation can better preserve the semantics of an edit as the underlying surface changes. Details of our implementation are described, including an efficient procedural mesh data structure.

In this paper, we propose a new constrained interpolation profile (CIP) method that is stable and accurate but requires less amount of computation compared to existing CIP-based solvers. CIP is a high-order fluid advection solver that can reproduce rich details of fluids. It has third-order accuracy but its computation is performed over a compact stencil. These advantageous features of CIP are, however, diluted by the following two shortcomings: (1) CIP contains a defect in the utilization of the grid data, which makes the method suitable only for simulations with a tight CFL restriction; and (2) CIP does not guarantee unconditional stability. There have been several attempts to fix these problems in CIP, but they have been only partially successful. The solutions that fixed both problems ended up introducing other undesirable features, namely increased computation time and/or reduced accuracy. This paper proposes a novel modification of the original CIP method that fixes all of the above problems without increasing the computational load or reducing the accuracy. Both quantitative and visual experiments were performed to test the performance of the new CIP in comparison to existing fluid solvers. The results show that the proposed method brings significant improvements in both accuracy and speed.

We present a technique for steganography in polygonal meshes. Our method hides a message in the indexed rep-resentation of a mesh by permuting the order in which faces and vertices are stored. The permutation is relative to a reference ordering that encoder and decoder derive from the mesh connectivity in a consistent manner. Our method is distortion-free because it does not modify the geometry of the mesh. Compared to previous steganographic methods for polygonal meshes our capacity is up to an order of magnitude better.Our steganography algorithm is universal and can be used instead of the standard permutation steganography algorithm on arbitrary datasets. The standard algorithm runs in (n2 log2 n log log n) time and achieves optimal O(nlog n) bit capacity on datasets with n elements. In contrast, our algorithm runs in O(n) time, achieves a capacity that is only one bit per element less than optimal, and is extremely simple to implement.

Metaballs are implicit surfaces widely used to model curved objects, represented by the isosurface of a density field defined by a set of points. Recently, the results of particle-based simulations have been often visualized using a large number of metaballs, however, such visualizations have high rendering costs. In this paper we propose a fast technique for rendering metaballs on the GPU. Instead of using polygonization, the isosurface is directly evaluated in a per-pixel manner. For such evaluation, all metaballs contributing to the isosurface need to be extracted along each viewing ray, on the limited memory of GPUs. We handle this by keeping a list of metaballs contributing to the isosurface and efficiently update it. Our method neither requires expensive precomputation nor acceleration data structures often used in existing ray tracing techniques. With several optimizations, we can display a large number of moving metaballs quickly.

We present a novel approach for real-time rendering of translucent surfaces. The computation of subsurface scattering is performed by first converting the integration over the 3D model surface into an integration over a 2D texture space and then applying importance sampling based on the irradiance stored in the texture. Such a conversion leads to a feasible GPU implementation and makes real-time frame rate possible. Our implementation shows that plausible images can be rendered in real time for complex translucent models with dynamic light and material properties. For objects with more apparent local effect, our approach generally requires more samples that may downgrade the frame rate. To deal with this case, we decompose the integration into two parts, one for local effect and the other for global effect, which are evaluated by the combination of available methods [DS03, MKB* 03a] and our texture space importance sampling, respectively. Such a hybrid scheme is able to steadily render the translucent effect in real time with a fixed amount of samples.

State-of-the-art car paint shows not only interesting and subtle angular dependency but also significant spatial variation. Especially in sunlight these variations remain visible even for distances up to a few meters and give the coating a strong impression of depth which cannot be reproduced by a single BRDF model and the kind of procedural noise textures typically used. Instead of explicitly modeling the responsible effect particles we propose to use image-based reflectance measurements of real paint samples and represent their spatial varying part by Bidirectional Texture Functions (BTF). We use classical BRDF models like Cook-Torrance to represent the reflection behavior of the base paint and the highly specular finish and demonstrate how the parameters of these models can be derived from the BTF measurements. For rendering, the image-based spatially varying part is compressed and efficiently synthesized. This paper introduces the first hybrid analytical and image-based representation for car paint and enables the photo-realistic rendering of all significant effects of highly complex coatings.

The viewfinder of a digital camera has traditionally been used for one purpose: to display to the user a preview of what is seen through the camera s lens. High quality cameras are now available on devices such as mobile phones and PDAs, which provide a platform where the camera is a programmable device, enabling applications such as online computational photography, computer vision-based interactive gaming, and augmented reality. For such online applications, the camera viewfinder provides the user s main interaction with the environment. In this paper, we describe an algorithm for aligning successive viewfinder frames. First, an estimate of inter-frame translation is computed by aligning integral projections of edges in two images. The estimate is then refined to compute a full 2D similarity transformation by aligning point features. Our algorithm is robust to noise, never requires storing more than one viewfinder frame in memory, and runs at 30 frames per second on standard smartphone hardware. We use viewfinder alignment for panorama capture, low-light photography, and a camera-based game controller.

In this paper we present a practical, simple and robust method to acquire the spatially-varying illumination of a real-world scene. The basic idea of the proposed method is to acquire the radiance distribution of the scene using high-dynamic range images of two reflective balls. The use of two light probes instead of a single one allows to estimate, not only the direction and intensity of the light sources, but also the actual position in space of the light sources. To robustly achieve this goal we first rectify the two input spherical images, then, using a region-based stereo matching algorithm, we establish correspondences and compute the position of each light. The radiance distribution so obtained can be used for augmented reality applications, photo-realistic rendering and accurate reflectance properties estimation. The accuracy and the effectiveness of the method have been tested by measuring the computed light position and rendering synthetic version of a real object in the same scene. The comparison with standard method that uses a simple spherical lighting environment is also shown.

We present a practical algorithm for sampling the product of environment map lighting and surface reflectance. Our method builds on wavelet-based importance sampling, but has a number of important advantages over previous methods. Most importantly, we avoid using precomputed reflectance functions by sampling the BRDF on-the-fly. Hence, all types of materials can be handled, including anisotropic and spatially varying BRDFs, as well as procedural shaders. This also opens up for using very high resolution, uncompressed, environment maps. Our results show that this gives a significant reduction of variance compared to using lower resolution approximations. In addition, we study the wavelet product, and present a faster algorithm geared for sampling purposes. For our application, the computations are reduced to a simple quadtree-based multiplication. We build the BRDF approximation and evaluate the product in a single tree traversal, which makes the algorithm both faster and more flexible than previous methods.

The goal of texture synthesis is to generate an arbitrarily large high-quality texture from a small input sample. Generally, it is assumed that the input image is given as a flat, square piece of texture, thus it has to be carefully prepared from a picture taken under ideal conditions. Instead we would like to extract the input texture from any surface from within an arbitrary photograph. This introduces several challenges: Only parts of the photograph are covered with the texture of interest, perspective and scene geometry introduce distortions, and the texture is non-uniformly sampled during the capture process. This breaks many of the assumptions used for synthesis.In this paper we combine a simple novel user interface with a generic per-pixel synthesis algorithm to achieve high-quality synthesis from a photograph. Our interface lets the user locally describe the geometry supporting the textures by combining rational Bezier patches. These are particularly well suited to describe curved surfaces under projection. Further, we extend per-pixel synthesis to account for arbitrary texture sparsity and distortion, both in the input image and in the synthesis output. Applications range from synthesizing textures directly from photographs to high-quality texture completion.

We present a technique for coupling simulated fluid phenomena that interact with real dynamic scenes captured as a binocular video sequence. We first process the binocular video sequence to obtain a complete 3D reconstruction of the scene, including velocity information. We use stereo for the visible parts of 3D geometry and surface completion to fill the missing regions. We then perform fluid simulation within a 3D domain that contains the object, enabling one-way coupling from the video to the fluid. In order to maintain temporal consistency of the reconstructed scene and the animated fluid across frames, we develop a geometry tracking algorithm that combines optic flow and depth information with a novel technique for velocity completion . The velocity completion technique uses local rigidity constraints to hypothesize a motion field for the entire 3D shape, which is then used to propagate and filter the reconstructed shape over time. This approach not only generates smoothly varying geometry across time, but also simultaneously provides the necessary boundary conditions for one-way coupling between the dynamic geometry and the simulated fluid. Finally, we employ a GPU based scheme for rendering the synthetic fluid in the real video, taking refraction and scene texture into account.