A survey of real-time crowd rendering

In this survey we review, classify and compare existing approaches for real-time crowd rendering. We first overview character animation techniques, as they are highly tied to crowd rendering performance, and then we analyze the state of the art in crowd rendering. We discuss different representations for level-of-detail (LoD) rendering of animated characters, including polygon-based, point-based, and image-based techniques, and review different criteria for runtime LoD selection. Besides LoD approaches, we review classic acceleration schemes, such as frustum culling and occlusion culling, and describe how they can be adapted to handle crowds of animated characters. We also discuss specific acceleration techniques for crowd rendering, such as primitive pseudo-instancing, palette skinning, and dynamic key-pose caching, which benefit from current graphics hardware. We also address other factors affecting performance and realism of crowds such as lighting, shadowing, clothing and variability. Finally we provide an exhaustive comparison of the most relevant approaches in the field.Peer ReviewedPostprint (author's final draft

Interactive inspection of complex multi-object industrial assemblies

The final publication is available at Springer via http://dx.doi.org/10.1016/j.cad.2016.06.005The use of virtual prototypes and digital models containing thousands of individual objects is commonplace in complex industrial applications like the cooperative design of huge ships. Designers are interested in selecting and editing specific sets of objects during the interactive inspection sessions. This is however not supported by standard visualization systems for huge models. In this paper we discuss in detail the concept of rendering front in multiresolution trees, their properties and the algorithms that construct the hierarchy and efficiently render it, applied to very complex CAD models, so that the model structure and the identities of objects are preserved. We also propose an algorithm for the interactive inspection of huge models which uses a rendering budget and supports selection of individual objects and sets of objects, displacement of the selected objects and real-time collision detection during these displacements. Our solution–based on the analysis of several existing view-dependent visualization schemes–uses a Hybrid Multiresolution Tree that mixes layers of exact geometry, simplified models and impostors, together with a time-critical, view-dependent algorithm and a Constrained Front. The algorithm has been successfully tested in real industrial environments; the models involved are presented and discussed in the paper.Peer ReviewedPostprint (author's final draft

Scalable Realtime Rendering and Interaction with Digital Surface Models of Landscapes and Cities

Interactive, realistic rendering of landscapes and cities differs substantially from classical terrain rendering. Due to the sheer size and detail of the data which need to be processed, realtime rendering (i.e. more than 25 images per second) is only feasible with level of detail (LOD) models. Even the design and implementation of efficient, automatic LOD generation is ambitious for such out-of-core datasets considering the large number of scales that are covered in a single view and the necessity to maintain screen-space accuracy for realistic representation. Moreover, users want to interact with the model based on semantic information which needs to be linked to the LOD model. In this thesis I present LOD schemes for the efficient rendering of 2.5d digital surface models (DSMs) and 3d point-clouds, a method for the automatic derivation of city models from raw DSMs, and an approach allowing semantic interaction with complex LOD models. The hierarchical LOD model for digital surface models is based on a quadtree of precomputed, simplified triangle mesh approximations. The rendering of the proposed model is proved to allow real-time rendering of very large and complex models with pixel-accurate details. Moreover, the necessary preprocessing is scalable and fast. For 3d point clouds, I introduce an LOD scheme based on an octree of hybrid plane-polygon representations. For each LOD, the algorithm detects planar regions in an adequately subsampled point cloud and models them as textured rectangles. The rendering of the resulting hybrid model is an order of magnitude faster than comparable point-based LOD schemes. To automatically derive a city model from a DSM, I propose a constrained mesh simplification. Apart from the geometric distance between simplified and original model, it evaluates constraints based on detected planar structures and their mutual topological relations. The resulting models are much less complex than the original DSM but still represent the characteristic building structures faithfully. Finally, I present a method to combine semantic information with complex geometric models. My approach links the semantic entities to the geometric entities on-the-fly via coarser proxy geometries which carry the semantic information. Thus, semantic information can be layered on top of complex LOD models without an explicit attribution step. All findings are supported by experimental results which demonstrate the practical applicability and efficiency of the methods

Techniques for an image space occlusion culling engine

In this work we present several techniques applied to implement an Image Space Software Occlusion Culling Engine to increase the speed of rendering general dynamic scenes with high depth complexity. This conservative culling method is based on a tiled Occlusion Map that is updated only when needed, deferring and even avoiding the expensive per pixel rasterization process. We show how the tiles become a useful way to increase the speed of visibility tests. Finally we describe how different parts of the engine were parallelized using OpenMP directives and SIMD instructions.Eje: Workshop Computación gráfica, imágenes y visualización (WCGIV)Red de Universidades con Carreras en Informática (RedUNCI

Conservative Visibility Preprocessing Using Extended Projections

International audienceVisualisation of very complex environments can be significantly accelerated using occlusion culling. In this paper we present a visibility preprocessing method which efficiently computes potentially visible geometry for volumetric viewing cells. We introduce novel extended projection operators, which permits efficient occlusion culling with respect to all viewpoints within a cell, and takes into account the combined occlusion effect of multiple occluders. We use extended projection of occluders onto a set of projection planes to create extended occlusion maps; we show how to efficiently test occludees against these occlusion maps to determine occlusion with respect to the entire cell. We also present an improved projection operator for certain specific but important configurations. An important advantage of our approach is that we can re-project extended projections onto a series of projection planes (via an occlusion sweep), and thus accumulate occlusion information from multiple blockers. This new approach allows the creation of effective occlusion maps for previously hard-to-treat scenes such as leaves of trees in a forest. Graphics hardware is used to accelerate both the extended projection and reprojection operations. We present a complete implementation of our preprocessing algorithm demonstrating significant speedup with respect to view-frustum culling only, without the computational overhead of on-line occlusion culling

Visibility computation through image generalization

This dissertation introduces the image generalization paradigm for computing visibility. The paradigm is based on the observation that an image is a powerful tool for computing visibility. An image can be rendered efficiently with the support of graphics hardware and each of the millions of pixels in the image reports a visible geometric primitive. However, the visibility solution computed by a conventional image is far from complete. A conventional image has a uniform sampling rate which can miss visible geometric primitives with a small screen footprint. A conventional image can only find geometric primitives to which there is direct line of sight from the center of projection (i.e. the eye) of the image; therefore, a conventional image cannot compute the set of geometric primitives that become visible as the viewpoint translates, or as time changes in a dynamic dataset. Finally, like any sample-based representation, a conventional image can only confirm that a geometric primitive is visible, but it cannot confirm that a geometric primitive is hidden, as that would require an infinite number of samples to confirm that the primitive is hidden at all of its points. ^ The image generalization paradigm overcomes the visibility computation limitations of conventional images. The paradigm has three elements. (1) Sampling pattern generalization entails adding sampling locations to the image plane where needed to find visible geometric primitives with a small footprint. (2) Visibility sample generalization entails replacing the conventional scalar visibility sample with a higher dimensional sample that records all geometric primitives visible at a sampling location as the viewpoint translates or as time changes in a dynamic dataset; the higher-dimensional visibility sample is computed exactly, by solving visibility event equations, and not through sampling. Another form of visibility sample generalization is to enhance a sample with its trajectory as the geometric primitive it samples moves in a dynamic dataset. (3) Ray geometry generalization redefines a camera ray as the set of 3D points that project at a given image location; this generalization supports rays that are not straight lines, and enables designing cameras with non-linear rays that circumvent occluders to gather samples not visible from a reference viewpoint. ^ The image generalization paradigm has been used to develop visibility algorithms for a variety of datasets, of visibility parameter domains, and of performance-accuracy tradeoff requirements. These include an aggressive from-point visibility algorithm that guarantees finding all geometric primitives with a visible fragment, no matter how small primitive\u27s image footprint, an efficient and robust exact from-point visibility algorithm that iterates between a sample-based and a continuous visibility analysis of the image plane to quickly converge to the exact solution, a from-rectangle visibility algorithm that uses 2D visibility samples to compute a visible set that is exact under viewpoint translation, a flexible pinhole camera that enables local modulations of the sampling rate over the image plane according to an input importance map, an animated depth image that not only stores color and depth per pixel but also a compact representation of pixel sample trajectories, and a curved ray camera that integrates seamlessly multiple viewpoints into a multiperspective image without the viewpoint transition distortion artifacts of prior art methods

Massive model visualization: An investigation into spatial partitioning

The current generation of visualization software is incapable of handling the interactive rendering of arbitrarily large models. While many solutions have been proposed for Massive Model Visualization, very few are able to achieve the full capabilities needed for a computer visualization solution. In most cases this is due to overly complex approaches that, while achieving impressive frame rates, make it virtually impossible to implement features like part manipulation. What is needed is a simple approach with rendering performance bounded by screen complexity not model size, with primitive traceability to the original model to facilitate part manipulation, and capability to be modified in near-real-time. This thesis introduces MMDr, a simple system to achieve interactive frame rates on extremely large data sets, while retaining support for most if not all the features required for a computer visualization solution

Real-time rendering of cities at night

En synthèse d’images, déterminer la couleur d’une surface au pixel d’une image doit considérer toutes les sources de lumière de la scène pour évaluer leur contribution lumineuse sur la surface en question. Cette évaluation de la visibilité et en l’occurrence de la radiance incidente des sources de lumière est très coûteuse. Elle n’est généralement pas traitée pour chaque source de lumière en rendu temps-réel. Une ville en pleine nuit est un exemple de telle scène comportant une grande quantité de sources de lumière pour lesquelles les rendus temps-réel modernes ne peuvent pas évaluer la visibilité de toutes les sources de lumière individuelles. Nous présentons une technique exploitant la cohérence spatiale des villes et la co-hérence temporelle des rendus temps-réel pour accélérer le calcul de la visibilité des sources de lumière. Notre technique de visibilité profite des bloqueurs naturels et pré-dominants de la ville pour rapidement réduire la liste de sources de lumière à évaluer etainsi, accélérer le calcul de la visibilité en assumant des bloqueurs sous forme de boîtes alignées majoritairement selon certains axes dominants. Pour garantir la propagation des occultations, nous fusionnons les bloqueurs adjacents dans un seul et même bloqueur conservateur en termes d’occultations. Notre technique relie la visibilité de la caméra avec la visibilité des surfaces pour réduire le nombre d’évaluations à effectuer à chaque rendu, et ne calcule la visibilité que pour les surfaces visibles du point de vue de la caméra. Finalement, nous intégrons la technique de visibilité avec une technique de rendu réaliste, Lightcuts, qui a été mise à jour sur GPU dans un scénario de rendu temps-réel. Même si notre technique ne permettra pas d’atteindre le temps-réel en général dans une scène complexe, elle réduit suffisamment les contraintes pour espérer y arriver un jour.In image synthesis, to determine the final color of a surface at a specific image pixel,we must consider all potential light sources and evaluate if they contribute to the illumination. Since such evaluation is slow, real-time renderers traditionally do not evaluate each light source, and instead preemptively choose locally important light sources for which to evaluate visibility. A city at night is such a scene containing many light sources for which modern real-time renderers cannot allow themselves to evaluate every light source at every frame.We present a technique exploiting spatial coherency in cities and temporal coherency of real-time walkthroughs to reduce visibility evaluations in such scenes. Our technique uses the natural and predominant occluders of a city to efficiently reduce the number of light sources to evaluate. To further accelerate the evaluation we project the bounding boxes of buildings instead of their detailed model (these boxes should be oriented mostly along a few directions), and fuse adjacent occluders on an occlusion plane to form larger conservative occluders. Our technique also integrates results from camera visibility to further reduce the number of visibility evaluations executed per frame, and evaluates visible light sources for facades visible from the point of view of the camera. Finally, we integrate an offline rendering technique, Lightcuts, by adapting it to real-time GPU rendering to further save on rendering time.Even though our technique does not achieve real-time frame rates in a complex scene,it reduces the complexity of the problem enough so that we can hope to achieve such frame rates one day