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Origamic architecture (OA) is a form of papercraft that involves cutting and folding a single sheet of paper to produce a 3D pop-up, and is commonly used to depict architectural structures. Because of the strict geometric and physical constraints, OA design requires considerable skill and effort. In this paper, we present a method to automatically generate an OA design that closely depicts an input 3D model. Our algorithm is guided by a novel set of geometric conditions to guarantee the foldability and stability of the generated pop-ups. The generality of the conditions allows our algorithm to generate valid pop-up structures that are previously not accounted for by other algorithms. Our method takes a novel image-domain approach to convert the input model to an OA design. It performs surface segmentation of the input model in the image domain, and carefully represents each surface with a set of parallel patches. Patches are then modified to make the entire structure foldable and stable. Visual and quantitative comparisons of results have shown our algorithm to be significantly better than the existing methods in the preservation of contours, surfaces, and volume. The designs have also been shown to more closely resemble those created by real artists.

This paper proposes an image-based painterly rendering algorithm for automatically synthesizing an image with color ink diffusion. We suggest a mathematical model with a physical base to simulate the phenomenon of color colloidal ink diffusing into absorbent paper. Our algorithm contains three main parts: a feature extraction phase, a Kubelka-Munk (KM) color mixing phase, and a color ink diffusion synthesis phase. In the feature extraction phase, the information of the reference image is simplified by luminance division and color segmentation. In the color mixing phase, the KM theory is employed to approximate the result when one pigment is painted upon another pigment layer. Then, in the color ink diffusion synthesis phase, the physically-based model that we propose is employed to simulate the result of color ink diffusion in absorbent paper using a texture synthesis technique. Our image-based ink diffusing rendering (IBCIDR) algorithm eliminates the drawback of conventional Chinese ink simulations, which are limited to the black ink domain, and our approach demonstrates that, without using any strokes, a color image can be automatically converted to the diffused ink style with a visually pleasing appearance.

This paper introduces a novel photometric compensation technique for inter-projector luminance and chrominance variations. Although it sounds as a classical technical issue, to the best of our knowledge there is no existing solution to alleviate the spatial non-uniformity among strongly heterogeneous projectors at perceptually acceptable quality. Primary goal of our method is increasing the perceived seamlessness of the projection system by automatically generating an improved and consistent visual quality. It builds upon the existing research of multi-projection systems, but instead of working with perceptually non-uniform color spaces such as CIEXYZ, the overall computation is carried out using the RLab [10, pp. 243–254] color appearance model which models the color processing in an adaptive, perceptual manner. Besides, we propose an adaptive color gamut acquisition, spatially varying gamut mapping, and optimization framework for edge blending. The paper describes the overall workflow and detailed algorithm of each component, followed by an evaluation validating the proposed method. The experimental results both qualitatively and quantitatively show the proposed method significant improved the visual quality of projected results of a multi-projection display with projectors with severely heterogeneous color processing.

Dynamic projection mapping for moving objects has attracted much attention in recent years. However, conventional approaches have faced some issues, such as the target objects being limited to rigid objects, and the limited moving speed of the targets. In this paper, we focus on dynamic projection mapping onto rapidly deforming non-rigid surfaces with a speed sufficiently high that a human does not perceive any misalignment between the target object and the projected images. In order to achieve such projection mapping, we need a high-speed technique for tracking non-rigid surfaces, which is still a challenging problem in the field of computer vision. We propose the Deformable Dot Cluster Marker (DDCM), a novel fiducial marker for high-speed tracking of non-rigid surfaces using a high-frame-rate camera. The DDCM has three performance advantages. First, it can be detected even when it is strongly deformed. Second, it realizes robust tracking even in the presence of external and self occlusions. Third, it allows millisecond-order computational speed. Using DDCM and a high-speed projector, we realized dynamic projection mapping onto a deformed sheet of paper and a T-shirt with a speed sufficiently high that the projected images appeared to be printed on the objects.

This paper presents an approach for non-contact haptic augmentation with spatial augmented reality (SAR). We construct a thermo-visual projection system by combining a standard RGB projector and a fabricated infrared (IR) projector. The primary contribution of this paper is that we conduct thorough psychophysical experiments to investigate a design guideline for spatiotemporal projection patterns for both RGB and IR projectors to render a warm object with high presence. We develop application systems to evaluate the validity of the proposed system and design guideline. The evaluation results demonstrate that the proposed system can render warm objects with significantly higher presence than a standard SAR system.

3D reconstruction from single-view images is a long-standing research problem. To date, there are various methods based on point clouds and volumetric representations. In spite of success in 3D models generation, it is quite challenge for these approaches to deal with models with complex topology and fine geometric details. Thanks to the recent advance of deep shape representations,learning the structure and detail representation using deep neural networks is a promising direction. In this paper, we propose a novel approach named STD-Net to reconstruct 3D models utilizing mesh representation that is well suited for characterizing complex structures and geometry details. Our method consists of (1) an auto-encoder network for recovering the structure of an object with bounding box representation from a single-view image; (2) a topology-adaptive GCN for updating vertex position for meshes of complex topology; and (3) a unified mesh deformation block that deforms the structural boxes into structure-aware meshes. Evaluation on ShapeNet shows that STD-Net has better performance than state-of-the-art methods in reconstructing complex structures and fine geometric details.

Branched covering spaces are a mathematical concept which originates from complex analysis and topology and has applications in tensor field topology and geometry remeshing. Given a manifold surface and an $N$ -way rotational symmetry field, a branched covering space is a manifold surface that has an $N$ -to-1 map to the original surface except at the ramification points , which correspond to the singularities in the rotational symmetry field. Understanding the notion and mathematical properties of branched covering spaces is important to researchers in tensor field visualization and geometry processing, and their application areas. In this paper, we provide a framework to interactively design and visualize the branched covering space (BCS) of an input mesh surface and a rotational symmetry field defined on it. In our framework, the user can visualize not only the BCSs but also their construction process. In addition, our system allows the user to design the geometric realization of the BCS using mesh deformation techniques as well as connecting tubes. This enables the user to verify important facts about BCSs such as that they are manifold surfaces around singularities, as well as the Riemann-Hurwitz formula which relates the Euler characteristic of the BCS to that of the original mesh. Our system is evaluated by student researchers in scientific visualization and geometry processing as well as faculty members in mathematics at our university who teach topology. We include their evaluations and feedback in the paper.

The state-of-the-art optical see-through head-mounted displays (OST-HMD) for augmented reality applications lack the ability to render correct light interaction behavior between digital and physical objects, known as mutual occlusion capability. This paper presents a novel optical architecture for enabling a compact, high performance, occlusion-capable optical see-through head-mounted display (OCOST-HMD) with correct, pupil-matched viewing perspective. The proposed design utilizes a single-layer, double-pass architecture, offering a compact OCOST-HMD solution that is capable of rendering per-pixel mutual occlusion, a correctly pupil-matched viewing between virtual and real views, and a very wide see-through field of view (FOV). Based on this architecture, we demonstrate a design embodiment and a compact prototype implementation. The prototype offers a virtual display with an FOV of 34 by 22, an angular resolution of 1.06 arc minutes per pixel, and an average image contrast greater than 40% at the Nyquist frequency of 53 cycles/mm. Further, the prototype system affords a wide see-though FOV of 90 by 50, within which about 40 diagonally is occlusion-enabled, along with an angular resolution of 1.0 arc minutes, comparable to a 20/20 vision and a dynamic range greater than 100:1. Lastly, we composed a quantitative color study that compares the effects of occlusion between a conventional HMD system and our OCOST-HMD system and the resulting response exhibited in different studies.

International audience; We systematically reviewed 64 user-study papers on data glyphs to help researchers and practitioners gain an informed understanding of tradeoffs in the glyph design space. The glyphs we consider are individual representations of multi-dimensional data points, often meant to be shown in small-multiple settings. Over the past 60 years many different glyph designs were proposed and many of these designs have been subjected to perceptual or comparative evaluations. Yet, a systematic overview of the types of glyphs and design variations tested, the tasks under which they were analyzed, or even the study goals and results does not yet exist. In this paper we provide such an overview by systematically sampling and tabulating the literature on data glyph studies, listing their designs, questions, data, and tasks. In addition we present a concise overview of the types of glyphs and their design characteristics analyzed by researchers in the past, and a synthesis of the study results. Based on our meta analysis of all results we further contribute a set of design implications and a discussion on open research directions.

In this paper, we describe a novel approach for applying texture mapping to volumetric data sets. In contrast to previous approaches, the presented technique enables a unified integration of 2D and 3D textures and thus allows to emphasize material boundaries as well as volumetric regions within a volumetric data set at the same time. One key contribution of this paper is a parametrization technique for volumetric data sets, which takes into account material boundaries and volumetric regions. Using this technique, the resulting parametrizations of volumetric data sets enable texturing effects which create a higher degree of realism in volume rendered images. We evaluate the quality of the parametrization and demonstrate the usefulness of the proposed concepts by combining volumetric texturing with volumetric lighting models to generate photorealistic volume renderings. Furthermore, we show the applicability in the area of illustrative visualization.

Closed geodesics, or geodesic loops, are crucial to the study of differential topology and differential geometry. Although the existence and properties of closed geodesics on smooth surfaces have been widely studied in mathematics community, relatively little progress has been made on how to compute them on polygonal surfaces. Most existing algorithms simply consider the mesh as a graph and so the resultant loops are restricted only on mesh edges, which are far from the actual geodesics. This paper is the first to prove the existence and uniqueness of geodesic loop restricted on a closed face sequence; it contributes also with an efficient algorithm to iteratively evolve an initial closed path on a given mesh into an exact geodesic loop within finite steps. Our proposed algorithm takes only an O(k) space complexity and an O(mk) time complexity (experimentally), where m is the number of vertices in the region bounded by the initial loop and the resultant geodesic loop, and k is the average number of edges in the edge sequences that the evolving loop passes through. In contrast to the existing geodesic curvature flow methods which compute an approximate geodesic loop within a predefined threshold, our method is exact and can apply directly to triangular meshes without needing to solve any differential equation with a numerical solver; it can run at interactive speed, e.g., in the order of milliseconds, for a mesh with around 50K vertices, and hence, significantly outperforms existing algorithms. Actually, our algorithm could run at interactive speed even for larger meshes. Besides the complexity of the input mesh, the geometric shape could also affect the number of evolving steps, i.e., the performance. We motivate our algorithm with an interactive shape segmentation example shown later in the paper.

In recent years, many volumetric illumination models have been proposed, which have the potential to simulate advanced lighting effects and thus support improved image comprehension. Although volume ray-casting is widely accepted as the volume rendering technique which achieves the highest image quality, so far no volumetric illumination algorithm has been designed to be directly incorporated into the ray-casting process. In this paper we propose image plane sweep volume illumination (IPSVI), which allows the integration of advanced illumination effects into a GPU-based volume ray-caster by exploiting the plane sweep paradigm. Thus, we are able to reduce the problem complexity and achieve interactive frame rates, while supporting scattering as well as shadowing. Since all illumination computations are performed directly within a single rendering pass, IPSVI does not require any preprocessing nor does it need to store intermediate results within an illumination volume. It therefore has a significantly lower memory footprint than other techniques. This makes IPSVI directly applicable to large data sets. Furthermore, the integration into a GPU-based ray-caster allows for high image quality as well as improved rendering performance by exploiting early ray termination. This paper discusses the theory behind IPSVI, describes its implementation, demonstrates its visual results and provides performance measurements.

Simulating shadow interactions between real and virtual objects is important for augmented reality (AR), in which accurately and efficiently detecting real shadows from live videos is a crucial step. Most of the existing methods are capable of processing only scenes captured under a fixed viewpoint. In contrast, this paper proposes a new framework for shadow detection in live outdoor videos captured under moving viewpoints. The framework splits each frame into a tracked region, which is the region tracked from the previous video frame through optical flow analysis, and an emerging region, which is newly introduced into the scene due to the moving viewpoint. The framework subsequently extracts features based on the intensity profiles surrounding the boundaries of candidate shadow regions. These features are then utilized to both correct erroneous shadow boundaries for the tracked region and to detect shadow boundaries for the emerging region by a Bayesian learning module. To remove spurious shadows, spatial layout constraints are further considered for emerging regions. The experimental results demonstrate that the proposed framework outperforms the state-of-the-art shadow tracking and detection algorithms on a variety of challenging cases in real time, including shadows on backgrounds with complex textures, nonplanar shadows, fast-moving shadows with changing typologies, and shadows cast by nonrigid objects. The quantitative experiments show that our method outperforms the best existing method, achieving a 33.3% increase in the average F_{measure}. Coupled with an image-based shadow-casting method, the proposed framework generates realistic shadow interaction results. This capability will be particularly beneficial for supporting AR.

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/

Just as we can work with two-dimensional floor plans to communicate 3D architectural design, we can exploit reduced- dimension shadows to manipulate the higher-dimensional objects generating the shadows. In particular, by taking advantage of physically reactive 3D shadow-space controllers, we can transform the task of interacting with 4D objects to a new level of physical reality. We begin with a teaching tool that uses 2D knot diagrams to manipulate the geometry of 3D mathematical knots via their projections; our unique 2D haptic interface allows the user to become familiar with sketching, editing, exploration, and manipulation of 3D knots rendered as projected images on a 2D shadow space. By combining graphics and collision-sensing haptics, we can enhance the 2D shadow-driven editing protocol to successfully leverage 2D pen-and-paper or blackboard skills. Building on the reduced-dimension 2D editing tool for manipulating 3D shapes, we develop the natural analogy to produce a reduced-dimension 3D tool for manipulating 4D shapes. By physically modeling the correct properties of 4D surfaces, their bending forces, and their collisions in the 3D haptic controller interface, we can support full-featured physical exploration of 4D mathematical objects in a manner that is otherwise far beyond the experience accessible to human beings. As far as we are aware, this paper reports the first interactive system with force-feedback that provides "4D haptic visualization" permitting the user to model and interact with 4D cloth-like objects.

International audience; This paper focuses on the 3D shape recovery and augmented reality on elastic objects with self-occlusions handling, using only single view images. Shape recovery from a monocular video sequence is an underconstrained problem and many approaches have been proposed to enforce constraints and resolve the ambiguities. State-of-the art solutions enforce smoothness or geometric constraints, consider specific deformation properties such as inextensibility or resort to shading constraints. However, few of them can handle properly large elastic deformations. We propose in this paper a real-time method that uses a mechanical model and able to handle highly elastic objects. The problem is formulated as an energy minimization problem accounting for a non-linear elastic model constrained by external image points acquired from a monocular camera. This method prevents us from formulating restrictive assumptions and specific constraint terms in the minimization. In addition, we propose to handle self-occluded regions thanks to the ability of mechanical models to provide appropriate predictions of the shape. Our method is compared to existing techniques with experiments conducted on computer-generated and real data that show the effectiveness of recovering and augmenting 3D elastic objects. Additionally, experiments in the context of minimally invasive liver surgery are also provided and results on deformations with the presence of self-occlusions are exposed.

This paper presents a method for occlusion-free animation of geographical landmarks, and its application to a new type of car navigation system in which driving routes of interest are always visible. This is achieved by animating a nonperspective image where geographical landmarks such as mountain tops and roads are rendered as if they are seen from different viewpoints. The technical contribution of this paper lies in formulating the nonperspective terrain navigation as an inverse problem of continuously deforming a 3D terrain surface from the 2D screen arrangement of its associated geographical landmarks. The present approach provides a perceptually reasonable compromise between the navigation clarity and visual realism where the corresponding nonperspective view is fully augmented by assigning appropriate textures and shading effects to the terrain surface according to its geometry. An eye tracking experiment is conducted to prove that the present approach actually exhibits visually-pleasing navigation frames while users can clearly recognize the shape of the driving route without occlusion, together with the spatial configuration of geographical landmarks in its neighborhood.

This paper presents a novel method for volume rendering of unstructured grids. Previously, we introduced an algorithm for perspective-correct interpolation of barycentric coordinates and computing polynomial attenuation integrals for a projected tetrahedron using graphics hardware. In this paper, we enhance the algorithm by providing a simple and efficient method to compute the projected shape (silhouette) and tessellation of a tetrahedron, in perspective and orthographic projection models. Our tessellation algorithm is published for the first time. Compared with works of other groups on rendering unstructured grids, the main contributions of this work are: 1) A new algorithm for finding the silhouette of a projected tetrahedron. 2) A method for interpolating barycentric coordinates and thickness on the faces of the tetrahedron. 3) Visualizing higher-order attenuation functions using GPU without preintegration. 4) Capability of applying shape deformations to a rendered tetrahedral mesh without significant performance loss. Our visualization model is independent of depth-sorting of the cells. We present imaging and timing results of our implementation, and an application in time-critical "2D-3D" deformable registration of anatomical models. We discuss the impact of using higher-order functions on quality and performance.

This paper proposes a novel approach for smoothing surfaces represented by triangular meshes. The proposed method is a two-step procedure: surface normal smoothing through fuzzy vector median (FVM) filtering followed by integration of surface normals for vertex position update based on the least square error (LSE) criteria. Median and Order Statistic-based filters are extensively used in signal processing, especially image processing, due to their ability to reject outliers and preserve features such as edges and monotonic regions. More recently, fuzzy ordering theory has been introduced to allow averaging among similarly valued samples. Fuzzy ordering theory leads naturally to the fuzzy median, which yields improved noise smoothing over traditional crisp median filters. This paper extends the fuzzy ordering concept to vector-based data and introduces the fuzzy vector median filter. The application of FVM filters to surface normal smoothing yields improved results over previously introduced normal smoothing algorithms. The improved filtering results, coupled with LSE vertex position update, produces surface smoothing that minimizes the effects of noise while simultaneously preserving detail features. The proposed method is simple to implement and relatively fast. Simulation results are presented showing the performance of the proposed method and its advantages over commonly used surface smoothing algorithms. Additionally, optimization procedures for FVM filters are derived and evaluated.

This paper describes an efficient algorithm to model the light attenuation due to a participating media with low albedo. Here, we consider the light attenuation along a ray, as well as the light attenuation emanating from a surface. The light attenuation is modeled using a splatting volume renderer for both the viewer and the light source. During the rendering, a 2D shadow buffer accumulates the light attenuation. We first summarize the basic shadow algorithm using splatting. Then, an extension of the basic shadow algorithm for projective textured light sources is described. The main part of this paper is an analytic soft shadow algorithm based on convolution techniques. We describe and discuss the soft shadow algorithm, and generate soft shadows, including umbra and penumbra, for extended light sources.

International audience; The goal of Mixed Reality (MR) is to achieve a seamless and realistic blending between real and virtual worlds. This requires the estimation of reflectance properties and lighting characteristics of the real scene. One of the main challenges within this task consists in recovering such properties using a single RGB-D camera. In this paper, we introduce a novel framework to recover both the position and color of multiple light sources as well as the specular reflectance of real scene surfaces. This is achieved by detecting and incorporating information from both specular reflections and cast shadows. Our approach is capable of handling any textured surface and considers both static and dynamic light sources. Its effectiveness is demonstrated through a range of applications including visually-consistent mixed reality scenarios (e.g. correct real specularity removal, coherent shadows in terms of shape and intensity) and retexturing where the texture of the scene is altered whereas the incident lighting is preserved.

Scientific ray tracing now can include realistic shading and material properties, but tracing rays of various depths to conclusion through partitioned data is inefficient. For such data, many ray scheduling methods have demonstrated improved rendering performance. However, synchronicity and non-adaptivity inherent in prior methods hinder further performance optimizations. In this paper, we attempt to relax these constraints. Specifically, we incorporate prediction models capable of dynamically adjusting levels of speculation in ray-data queries, making ray scheduling highly adaptable to a spectrum of scene characteristics. In addition, we organize rays in a tree of speculation nodes, where speculation is coordinated pairwise within a subtree of adaptive ray groups, facilitating concurrency and parallelism. Compared to prior non-predictive methods, we achieve up to three times higher throughput for volume and geometry rendering on a distributed system, making our method fit for both interactive and offline applications.

In this paper, we present a novel implicit glyph shape representation, which models glyphs as shape primitives enclosed by quadratic curves, and naturally enables generating glyph images at arbitrary high resolutions. Experiments on font reconstruction and interpolation tasks verified that this structured implicit representation is suitable for describing both structure and style features of glyphs. Furthermore, based on the proposed representation, we design a simple yet effective disentangled network for the challenging one-shot font style transfer problem, and achieve the best results comparing to state-of-the-art alternatives in both quantitative and qualitative comparisons. Benefit from this representation, our generated glyphs have the potential to be converted to vector fonts through post-processing, reducing the gap between rasterized images and vector graphics. We hope this work can provide a powerful tool for 2D shape analysis and synthesis, and inspire further exploitation in implicit representations for 2D shape modeling.

This paper concerns stereoscopic virtual reality displays in which the head is tracked and the display is stationary, attached to a desk, tabletop or wall. These are called stereoscopic HTDs (head-tracked displays). Stereoscopic displays render two perspective views of a scene, each of which is seen by one eye of the user. Ideally, the user's natural visual system combines the stereo image pair into a single, 3D perceived image. Unfortunately, users often have difficulty fusing the stereo image pair. Researchers use a number of software techniques to reduce fusion problems. This paper geometrically examines and compares a number of these techniques and reaches the following conclusions: In interactive stereoscopic applications, the combination of view placement, scale, and either false eye separation or /spl alpha/-false eye separation can provide fusion control that is geometrically similar to image shifting and image scaling. However, in stereo HTDs, image shifting and image scaling also generate additional geometric artifacts that are not generated by the other methods. We anecdotally link some of these artifacts to exceeding the perceptual limitations of human vision. While formal perceptual studies are still needed, geometric analysis suggests that image shifting and image scaling may be less appropriate than the other methods for interactive, stereo HTDs.

In volume graphics, objects are represented by arrays or clusters of sampled 3D data. A volumetric object representation is necessary in computer modeling whenever interior structure affects an object's behavior or appearance. However, existing volumetric representations are not sufficient for modeling the behaviors expected in applications such as surgical simulation, where interactions between both rigid and deformable objects and the cutting, tearing, and repairing of soft tissues must be modeled in real time. Three-dimensional voxel arrays lack the sense of connectivity needed for complex object deformation, while finite element models and mass-spring systems require substantially reduced geometric resolution for interactivity and they can not be easily cut or carved interactively. This paper discusses a linked volume representation that enables physically realistic modeling of object interactions such as: collision detection, collision response, 3D object deformation, and interactive object modification by carving, cutting, tearing, and joining. The paper presents a set of algorithms that allow interactive manipulation of linked volumes that have more than an order of magnitude more elements and considerably more flexibility than existing methods. Implementation details, results from timing tests, and measurements of material behavior are presented.

Virtual reality (VR) applications require high-performance rendering algorithms to efficiently render 3D scenes on the VR head-mounted display, to provide users with an immersive and interactive virtual environment. Foveated rendering provides a solution to improve the performance of rendering algorithms by allocating computing resources to different regions based on the human visual acuity, and renders images of different qualities in different regions. Rasterization-based methods and ray tracing methods can be directly applied to foveated rendering, but rasterization-based methods are difficult to estimate global illumination (GI), and ray tracing methods are inefficient for rendering scenes that contain paths with low probability. Photon mapping is an efficient GI rendering method for scenes with different materials. However, since photon mapping cannot dynamically adjust the rendering quality of GI according to the human acuity, it cannot be directly applied to foveated rendering. In this paper, we propose a foveated photon mapping method to render realistic GI effects in the foveal region. We use the foveated photon tracing method to generate photons with high density in the foveal region, and these photons are used to render high-quality images in the foveal region. We further propose a temporal photon management to select and update the valid foveated photons of the previous frame for improving our method's performance. Our method can render diffuse, specular, glossy and transparent materials to achieve effects specifically related to GI, such as color bleeding, specular reflection, glossy reflection and caustics. Our method supports dynamic scenes and renders high-quality GI in the foveal region at interactive rates.

Proper occlusion based rendering is very important to achieve realism in all indoor and outdoor Augmented Reality (AR) applications. This paper addresses the problem of fast and accurate dynamic occlusion reasoning by real objects in the scene for large scale outdoor AR applications. Conceptually, proper occlusion reasoning requires an estimate of depth for every point in augmented scene which is technically hard to achieve for outdoor scenarios, especially in the presence of moving objects. We propose a method to detect and automatically infer the depth for real objects in the scene without explicit detailed scene modeling and depth sensing (e.g. without using sensors such as 3D-LiDAR). Specifically, we employ instance segmentation of color image data to detect real dynamic objects in the scene and use either a top-down terrain elevation model or deep learning based monocular depth estimation model to infer their metric distance from the camera for proper occlusion reasoning in real time. The realized solution is implemented in a low latency real-time framework for video-see-though AR and is directly extendable to optical-see-through AR. We minimize latency in depth reasoning and occlusion rendering by doing semantic object tracking and prediction in video frames.

OVER the last decade or so, the related fields of virtual reality, augmented reality, and haptics have seen tremendous progress and expanded application domains. New graphics and haptic displays, faster and distributed computing hardware, better authoring software, and human factors studies lead to systems that are closer to meeting the user’s high expectations. The new awareness in the visualization and graphics community lead to a call for papers for this special iisue on haptics, virtual, and augmented reality of our transactions. The four guest editors and the editorial office had the demanding task of selecting 11 papers out of nearly 100 manuscripts that were received. We relied heavily on the many reviewers of this special issue and we would like to thank them warmly for the diligent work they did. One of the current challenges in virtual and augmented reality is omnidirectional stereo graphics, specifically the way to capture video that can then be seen in stereo, regardless of the user’s viewing direction. The special issue starts with the paper written by Tanaka and Tachi on “Tornado: Omnistereo Video Imaging with Rotating Optics.” The system uses two cameras and an optics assembly inside a rotating cylindrical shutter surface. Depending on the rotating speed, the stereo image is synthesized through optics (low rpm) or postprocessing (high rpm). The second paper, “Development of Anthropomorphic Multi-D.O.F. Master-Slave Arm for Mutual Telexistence” by Tadakuma, Asahara, Kajimoto, Kawakami, and Tachi, describes a novel robotic arm. The authors are working toward teleexistence, which places a physical avatar of the operator—a robot—in a remote location. Such technology enables humans to work in remote or hostile environments, such as contaminated sites, unstable mines, burning structures, or battlefields. Here, the authors describe the mechanical design and control algorithms for an anthropomorphic arm on such a robot. The operator controls the robot’s arm using an exoskeleton around his own arm and sees what the rest of the robot sees by using a headmounted display coupled with cameras on the robot’s head. Tadakuma et al. compared three control methods and found that impedance control was the most appropriate for their system. Another issue related to telepresence and distributed virtual environments is fast and smooth communication between remote locations. This is the subject of the paper “Data Streaming in Telepresence Environments” by Lamboray, Wurmlin, and Gross. Data streams in networked virtual environments are analyzed and classified according to their traffic characteristics. Special emphasis is placed on geometry enhanced (3D) video. The paper presents a simulated analysis of network latency and bandwidth occurring in a system that connects two CAVE-like environments and displays the user’s entire real body as an avatar. The 3D avatar model is constructed in real-time using computer vision techniques applied to the images of a collection of cameras that view the user. Remote collaboration in virtual environments is an important application area; the paper’s combination of a detailed system description and careful analysis will provide a solid basis for application development and future research in this area. A way to improve simulation response in distributed virtual environments is to reduce network load by incorporating more “intelligence” into object models (including avatars). This is the subject of the paper “Dynamic Interactions in Physically Realistic Collaborative Virtual Environments” by Jorissen, Wijnants, and Lamotte. Their approach uses inverse kinematics to provide more realism in avatar movements and make object interactions application independent. One way to further improve user-object interaction is to model its companion haptic feedback. In the paper “6-DOF Haptic Rendering Using Spatialized Normal Cone Search,” Johnson, Willemsen, and Cohen present a novel haptic rendering algorithm for displaying interaction forces and torques between two polygonal objects. By using spatialized normal cones, the algorithm detects collision robustly. It maintains local distance extrema between the virtual environment and the object moved by the haptic device to compute the resulting haptic feedback. The approach is demonstrated on models consisting of tens of thousands of triangles, tested on several complex geometric scenes, and applied to a virtual prototyping application. IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS, VOL. 11, NO. 6, NOVEMBER/DECEMBER 2005 611

International audience; Rendering participating media is important to the creation of photorealistic images. Participating media has a translucent aspect that comes from light being scattered inside the material. For materials with a small mean-free-path (mfp), multiple scattering effects dominate. Simulating these effects is computationally intensive, as it requires tracking a large number of scattering events inside the material. Existing approaches precompute multiple scattering events inside the material and store the results in a table. During rendering time, this table is used to compute the scattering effects. While these methods are faster than explicit scattering computation, they incur higher storage costs. In this paper, we present a new representation for double and multiple scattering effects that uses a neural network model. The scattering response from all homogeneous participating media is encoded into a neural network in a preprocessing step. At run time, the neural network is then used to predict the double and multiple scattering effects. We demonstrate the effects combined with Virtual Ray Lights (VRL), although our approach can be integrated with other rendering algorithms. Our algorithm is implemented on GPU. Double and multiple scattering effects for the entire participating media space are encoded using only 23.6 KB of memory. Our method achieves 50 ms per frame in typical scenes and provides results almost identical to the reference.

This paper presents a study of gradient estimation methods for rendering unstructured-mesh volume data. Gradient estimation is necessary for rendering shaded isosurfaces and specular highlights, which provide important cues for shape and depth. Gradient estimation has been widely studied and deployed for regular-grid volume data to achieve local illumination effects, but has been, otherwise, for unstructured-mesh data. As a result, most of the unstructured-mesh volume visualizations made so far were unlit. In this paper, we present a comprehensive study of gradient estimation methods for unstructured meshes with respect to their cost and performance. Through a number of benchmarks, we discuss the effects of mesh quality and scalar function complexity in the accuracy of the reconstruction, and their impact in lighting-enabled volume rendering. Based on our study, we also propose two heuristic improvements to the gradient reconstruction process. The first heuristic improves the rendering quality with a hybrid algorithm that combines the results of the multiple reconstruction methods, based on the properties of a given mesh. The second heuristic improves the efficiency of its GPU implementation, by restricting the computation of the gradient on a fixed-size local neighborhood.

Ray-triangle intersection is an important algorithm, not only in the field of realistic rendering (based on ray tracing) but also in physics simulation, collision detection, modeling, etc. Obviously, the speed of this well-defined algorithm's implementations is important because calls to such a routine are numerous in rendering and simulation applications. Contemporary fast intersection algorithms, which use SIMD instructions, focus on the intersection of ray packets against triangles. For intersection between single rays and triangles, operations such as horizontal addition or dot product are required. The SSE4 instruction set adds the dot product instruction which can be used for this purpose. This paper presents a new modification of the fast ray-triangle intersection algorithms commonly used, which-when implemented on SSE4-outperforms the current state-of-the-art algorithms. It also allows both a single ray and ray packet intersection calculation with the same precomputed data. The speed gain measurements are described and discussed in the paper.

This paper presents the first practical method for "origamizing? or obtaining the folding pattern that folds a single sheet of material into a given polyhedral surface without any cut. The basic idea is to tuck fold a planar paper to form a three-dimensional shape. The main contribution is to solve the inverse problem; the input is an arbitrary polyhedral surface and the output is the folding pattern. Our approach is to convert this problem into a problem of laying out the polygons of the surface on a planar paper by introducing the concept of tucking molecules. We investigate the equality and inequality conditions required for constructing a valid crease pattern. We propose an algorithm based on two-step mapping and edge splitting to solve these conditions. The two-step mapping precalculates linear equalities and separates them from other conditions. This allows an interactive manipulation of the crease pattern in the system implementation. We present the first system for designing three-dimensional origami, enabling a user can interactively design complex spatial origami models that have not been realizable thus far.

Image-based relighting, projector compensation and depth/normal reconstruction are three important tasks of projector-camera systems (ProCams) and spatial augmented reality (SAR). Although they share a similar pipeline of finding projector-camera image mappings, in tradition, they are addressed independently, sometimes with different prerequisites, devices and sampling images. In practice, this may be cumbersome for SAR applications to address them one-by-one. In this paper, we propose a novel end-to-end trainable model named DeProCams to explicitly learn the photometric and geometric mappings of ProCams, and once trained, DeProCams can be applied simultaneously to the three tasks. DeProCams explicitly decomposes the projector-camera image mappings into three subprocesses: shading attributes estimation, rough direct light estimation and photorealistic neural rendering. A particular challenge addressed by DeProCams is occlusion, for which we exploit epipolar constraint and propose a novel differentiable projector direct light mask. Thus, it can be learned end-to-end along with the other modules. Afterwards, to improve convergence, we apply photometric and geometric constraints such that the intermediate results are plausible. In our experiments, DeProCams shows clear advantages over previous arts with promising quality and meanwhile being fully differentiable. Moreover, by solving the three tasks in a unified model, DeProCams waives the need for additional optical devices, radiometric calibrations and structured light., Source code and supplementary material at: https://github.com/BingyaoHuang/DeProCams

There have been significant advances in capturing gigapixel panoramas (GPP). However, solutions for viewing GPPs on head-mounted displays (HMDs) are lagging: an immersive experience requires ultra-fast rendering while directly loading a GPP onto the GPU is infeasible due to limited texture memory capacity. In this paper, we present a novel out-of-core rendering technique that supports not only classic panning, tilting, and zooming but also dynamic refocusing for viewing a GPP on HMD. Inspired by the network package transmission mechanisms in distributed visualization, our approach employs hierarchical image tiling and on-demand data updates across the main and the GPU memory. We further present a multi-resolution rendering scheme and a refocused light field rendering technique based on RGBD GPPs with minimal memory overhead. Comprehensive experiments demonstrate that our technique is highly efficient and reliable, able to achieve ultra-high frame rates ( $> 50$ > 50 fps) even on low-end GPUs. With an embedded gaze tracker, our technique enables immersive panorama viewing experiences with unprecedented resolutions, field-of-view, and focus variations while maintaining smooth spatial, angular, and focal transitions.

The availability of commodity volumetric displays provides ordinary users with a new means of visualizing 3D data. Many of these displays are in the class of isotropically emissive light devices, which are designed to directly illuminate voxels in a 3D frame buffer, producing x-ray-like visualizations. While this technology can offer intuitive insight into a 3D object, the visualizations are perceptually different from what a computer graphics or visualization system would render on a 2D screen. This paper formalizes rendering on isotropically emissive displays and introduces a novel technique that emulates traditional rendering effects on isotropically emissive volumetric displays, delivering results that are much closer to what is traditionally rendered on regular 2D screens. Such a technique can significantly broaden the capability and usage of isotropically emissive volumetric displays. Our method takes a 3D data set or object as the input, creates an intermediate light field, and outputs a special 3D volume data set called a lumi-volume. This lumi-volume encodes approximated rendering effects in a form suitable for display with accumulative integrals along unobtrusive rays. When a lumi-volume is fed directly into an isotropically emissive volumetric display, it creates a 3D visualization with surface shading effects that are familiar to the users. The key to this technique is an algorithm for creating a 3D lumi-volume from a 4D light field. In this paper, we discuss a number of technical issues, including transparency effects due to the dimension reduction and sampling rates for light fields and lumi-volumes. We show the effectiveness and usability of this technique with a selection of experimental results captured from an isotropically emissive volumetric display, and we demonstrate its potential capability and scalability with computer-simulated high-resolution results.

This paper describes a method for constructing isosurface triangulations of sampled, volumetric, three-dimensional scalar fields. The resulting meshes consist of triangles that are of consistently high quality, making them well suited for accurate interpolation of scalar and vector-valued quantities, as required for numerous applications in visualization and numerical simulation. The proposed method does not rely on a local construction or adjustment of triangles as is done, for instance, in advancing wavefront or adaptive refinement methods. Instead, a system of dynamic particles optimally samples an implicit function such that the particles' relative positions can produce a topologically correct Delaunay triangulation. Thus, the proposed method relies on a global placement of triangle vertices. The main contributions of the paper are the integration of dynamic particles systems with surface sampling theory and PDE-based methods for controlling the local variability of particle densities, as well as detailing a practical method that accommodates Delaunay sampling requirements to generate sparse sets of points for the production of high-quality tessellations.

A major problem with interactive displays based on front projection is that users cast undesirable shadows on the display surface. This paper demonstrates that shadows can be muted by redundantly illuminating the display surface using multiple projectors, all mounted at different locations. However, this technique alone does not eliminate shadows: Multiple projectors create multiple dark regions on the surface (penumbral occlusions) and cast undesirable light onto the users. These problems can be solved by eliminating shadows and suppressing the light that falls on occluding users by actively modifying the projected output. This paper categorizes various methods that can be used to achieve redundant illumination, shadow elimination, and blinding light suppression and evaluates their performance.

In this paper we present a user-friendly sketching-based suggestive interface for untangling mathematical knots with complicated structures. Rather than treating mathematical knots as if they were 3D ropes, our interface is designed to assist the user to interact with knots with the right sequence of mathematically legal moves. Our knot interface allows one to sketch and untangle knots by proposing the Reidemeister moves, and can guide the user to untangle mathematical knots to the fewest possible number of crossings by suggesting the moves needed. The system highlights parts of the knot where the Reidemeister moves are applicable, suggests the possible moves, and constrains the user's drawing to legal moves only. This ongoing suggestion is based on a Reidemeister move analyzer, that reads the evolving knot in its Gauss code and predicts the needed Reidemeister moves towards the fewest possible number of crossings. For our principal test case of mathematical knot diagrams, this for the first time permits us to visualize, analyze, and deform them in a mathematical visual interface. In addition, understanding of a fairly long mathematical deformation sequence in our interface can be aided by visual analysis and comparison over the identified "key moments" where only critical changes occur in the sequence. Our knot interface allows users to track and trace mathematical knot deformation with a significantly reduced number of visual frames containing only the Reidemeister moves being applied. All these combine to allow a much cleaner exploratory interface for us to analyze and study mathematical knots and their dynamics in topological space.

This paper presents a vector painting system for digital artworks. We first propose Temporal Diffusion Curve (TDC), a new form of vector graphics, and a novel random-access solver for modeling the evolution of strokes. With the help of a procedural stroke processing function, the TDC strokes can achieve various shapes and effects for multiple art styles. Based on these, we build a painting system of great potential. Thanks to the random-access solver, our method has real-time performance regardless of the rendering resolution, provides straightforward editing possibilities on strokes both at runtime and afterward, and is effective and straightforward for art production. Compared with the previous Diffusion Curve, our method uses strokes as the basic graphics primitives, which are able to intersect each other and much more consistent with the intuition and painting habits of human. We finally demonstrate that professional artists can create multiple genres of artworks with our painting system.

The freeform architectural modeling process often involves two important stages: concept design and digital modeling. In the first stage, architects usually sketch the overall 3D shape and the panel layout on a physical or digital paper briefly. In the second stage, a digital 3D model is created using the sketch as a reference. The digital model needs to incorporate geometric requirements for its components, such as the planarity of panels due to consideration of construction costs, which can make the modeling process more challenging. In this work, we present a novel sketch-based system to bridge the concept design and digital modeling of freeform roof-like shapes represented as planar quadrilateral (PQ) meshes. Our system allows the user to sketch the surface boundary and contour lines under axonometric projection and supports the sketching of occluded regions. In addition, the user can sketch feature lines to provide directional guidance to the PQ mesh layout. Given the 2D sketch input, we propose a deep neural network to infer in real-time the underlying surface shape along with a dense conjugate direction field, both of which are used to extract the final PQ mesh. To train and validate our network, we generate a large synthetic dataset that mimics architect sketching of freeform quadrilateral patches. The effectiveness and usability of our system are demonstrated with quantitative and qualitative evaluation as well as user studies., To appear in IEEE Transactions on Visualization and Computer Graphics

This paper presents a new combinatorial approach to surface reconstruction with sharp features. Different from other postprocessing methods, the proposed method provides a systematic way to identify and reconstruct sharp features from unorganized sample points in one integrated reconstruction process. In addition, unlike other approximation methods, the reconstructed triangulated surface is guaranteed to pass through the original sample points. In this paper, the sample points in the sharp regions are defined as characteristic vertices (c-vertices), and their associated poles (c-poles) are used as a "sculptor" to extract triangles from a Delaunay structure for the sharp features. But, for smooth surface regions, an efficient region-growing scheme is used for triangle extraction and connection. Since only the c-poles associated with the sharp regions are used to participate in the Delaunay computation with the sample points, the proposed algorithm is adaptive in the sense that, given a sampled object with less sharp features, the triangulation becomes more efficient. To validate the proposed algorithm, some detailed illustrations are given. Experimental results show that it is robust and highly efficient.

The parameterization of a 3D mesh into a planar domain requires a distortion metric and a minimizing process. Most previous work has sought to minimize the average area distortion, the average angle distortion, or a combination of these. Typical distortion metrics can reflect the overall performance of parameterizations but discount high local deformations. This affects the performance of postprocessing operations such as uniform remeshing and texture mapping. This paper introduces a new metric that synthesizes the average distortions and the variances of both the area deformations and the angle deformations over an entire mesh. Experiments show that, when compared with previous work, the use of synthesized distortion metric performs satisfactorily in terms of both the average area deformation and the average angle deformation; furthermore, the area and angle deformations are distributed more uniformly. This paper also develops a new iterative process for minimizing the synthesized distortion, the coefficient-optimizing algorithm. At each iteration, rather than updating the positions immediately after the local optimization, the coefficient-optimizing algorithm first update the coefficients for the linear convex combination and then globally updates the positions by solving the Laplace system. The high performance of the coefficient-optimizing algorithm has been demonstrated in many experiments.

In the paper, we present a method for space-efficient representation of geometric tree models, which are provided as skeletons with radii attached to individual branch segments. The proposed approach uses a new differential 3D chain code to encode orientation changes of consecutive branch segments, which allows optimizing chain code generation for increased compressibility while maintaining control over the model reconstruction error. The presented method is the first to encode the complete branching geometry including the branch radii and provides level-of-detail construction directly from the chain code. It is demonstrated that by using interpolative encoding of the resulting tree descriptors and radii sequences, the storage requirements for geometric description of a mixed all-aged forest can be reduced to less than 15 percent of its raw size while preserving the structural fidelity of tree models.

This paper presents a novel surface registration technique using the spectrum of the shapes, which can facilitate accurate localization and visualization of non-isometric deformations of the surfaces. In order to register two surfaces, we map both eigenvalues and eigenvectors of the Laplace-Beltrami of the shapes through optimizing an energy function. The function is defined by the integration of a smoothness term to align the eigenvalues and a distance term between the eigenvectors at feature points to align the eigenvectors. The feature points are generated using the static points of certain eigenvectors of the surfaces. By using both the eigenvalues and the eigenvectors on these feature points, the computational efficiency is improved considerably without losing the accuracy in comparison to the approaches that use the eigenvectors for all vertices. In our technique, the variation of the shape is expressed using a scale function defined at each vertex. Consequently, the total energy function to align the two given surfaces can be defined using the linear interpolation of the scale function derivatives. Through the optimization of the energy function, the scale function can be solved and the alignment is achieved. After the alignment, the eigenvectors can be employed to calculate the point-to-point correspondence of the surfaces. Therefore, the proposed method can accurately define the displacement of the vertices. We evaluate our method by conducting experiments on synthetic and real data using hippocampus, heart, and hand models. We also compare our method with non-rigid Iterative Closest Point (ICP) and a similar spectrum-based methods. These experiments demonstrate the advantages and accuracy of our method.

Face sketch synthesis shows great applications in a lot of fields such as online entertainment and suspects identification. Existing face sketch synthesis methods learn the patch-wise sketch style from the training dataset containing photo-sketch pairs. These methods manipulate the whole process directly in the field of RGB space, which unavoidably results in unsmooth noises at patch boundaries. If denoising methods are used, the sketch edges would be blurred and face structures could not be restored. Recent researches of feature maps, which are the outputs of a certain neural network layer, have achieved great success in texture synthesis and artistic image generation. In this paper, we reformulate the face sketch synthesis problem into a neural network feature maps based optimization task. Our results accurately capture the sketch drawing style and make full use of the whole stylistic information hidden in the training dataset. Unlike former feature map based methods, we utilize the Enhanced 3D PatchMatch and cross-layer cost aggregation methods to obtain the target feature maps for the final results. Multiple experiments have shown that our approach imitates hand-drawn sketch style vividly, and has high-quality visual effects on CUHK, AR, XM2VTS and CUFSF face sketch datasets.

Unstructured data are collections of points with irregular topology, often represented through simplicial meshes, such as triangle and tetrahedral meshes. Whenever possible such representations are avoided in visualization since they are computationally demanding if compared with regular grids. In this work, we aim at simplifying the encoding and processing of simplicial meshes. The paper proposes TopoCluster, a new localized data structure for tetrahedral meshes. TopoCluster provides efficient computation of the connectivity of the mesh elements with a low memory footprint. The key idea of TopoCluster is to subdivide the simplicial mesh into clusters. Then, the connectivity information is computed locally for each cluster and discarded when it is no longer needed. We define two instances of TopoCluster. The first instance prioritizes time efficiency and provides only a modest savings in memory, while the second instance drastically reduces memory consumption up to an order of magnitude with respect to comparable data structures. Thanks to the simple interface provided by TopoCluster, we have been able to integrate both data structures into the existing Topological Toolkit (TTK) framework. As a result, users can run any plugin of TTK using TopoCluster without changing a single line of code.

Circular glyphs are used across disparate fields to represent multidimensional data. However, although these glyphs are extremely effective, creating them is often laborious, even for those with professional design skills. This paper presents GlyphCreator, an interactive tool for the example-based generation of circular glyphs. Given an example circular glyph and multidimensional input data, GlyphCreator promptly generates a list of design candidates, any of which can be edited to satisfy the requirements of a particular representation. To develop GlyphCreator, we first derive a design space of circular glyphs by summarizing relationships between different visual elements. With this design space, we build a circular glyph dataset and develop a deep learning model for glyph parsing. The model can deconstruct a circular glyph bitmap into a series of visual elements. Next, we introduce an interface that helps users bind the input data attributes to visual elements and customize visual styles. We evaluate the parsing model through a quantitative experiment, demonstrate the use of GlyphCreator through two use scenarios, and validate its effectiveness through user interviews.

Many geometric optimization problems contain manifold constraints that restrict the optimized vertices on some specified manifold surface. The constraints are highly nonlinear and non-convex, therefore existing methods usually suffer from a breach of condition or low optimization quality. In this paper, we present a novel divide-and-conquer methodology for manifold-constrained geometric optimization problems. Central to our methodology is to use local parameterizations to decouple the optimization with hard constraints, which transforms nonlinear constraints into linear constraints. We decompose the input mesh into a set of developable or nearly-developable overlapping patches with disc topology, then flatten each patch into the planar domain with very low isometric distortion, optimize vertices with linear constraints and recover the patch. Finally, we project it onto the constrained manifold surface. We demonstrate the applicability and robustness of our methodology through a variety of geometric optimization tasks. Experimental results show that our method performs much better than existing methods.

This paper addresses the problem of mesh super-resolution such that the geometry details which are not well represented in the low-resolution models can be recovered and well represented in the generated high-quality models. The main challenges of this problem are the non-regularity of 3D mesh representation and the high complexity of 3D shapes. We propose a deep neural network called GDR-Net to solve this ill-posed problem, which resolves the two challenges simultaneously. First, to overcome the non-regularity, we regress a displacement in radial basis function parameter space instead of the vertex-wise coordinates in the Euclidean space. Second, to overcome the high complexity, we apply the detail recovery process to small surface patches extracted from the input surface and obtain the overall high-quality mesh by fusing the refined surface patches. To train the network, we constructed a dataset composed of both real-world and synthetic scanned models, including high/low-quality pairs. Our experimental results demonstrate that GDR-Net works well for general models and outperforms previous methods for recovering geometric details.

Shader lamp systems augment the real environment by projecting new textures on known target geometries. In dynamic scenes, object tracking maintains the illusion if the physical and virtual objects are well aligned. However, traditional trackers based on texture or contour information are often distracted by the projected content and tend to fail. In this paper, we present a model-based tracking strategy, which directly takes advantage from the projected content for pose estimation in a projector-camera system. An iterative pose estimation algorithm captures and exploits visible distortions caused by object movements. In a closed-loop, the corrected pose allows the update of the projection for the subsequent frame. Synthetic frames simulating the projection on the model are rendered and an optical flow-based method minimizes the difference between edges of the rendered and the camera image. Since the thresholds automatically adapt to the synthetic image, a complicated radiometric calibration can be avoided. The pixel-wise linear optimization is designed to be easily implemented on the GPU. Our approach can be combined with a regular contour-based tracker and is transferable to other problems, like the estimation of the extrinsic pose between projector and camera. We evaluate our procedure with real and synthetic images and obtain very precise registration results.