Speeding up rendering of hybrid surface and volume models

Hybrid rendering of volume and polygonal model is an interesting feature of visualization systems, since it helps users to better understand the relationships between internal structures of the volume and fitted surfaces as well as external surfaces. Most of the existing bibliography focuses at the problem of correctly integrating in depth both types of information. The rendering method proposed in this paper is built on these previous results. It is aimed at solving a different problem: how to efficiently access to selected information of a hybrid model. We propose to construct a decision tree (the Rendering Decision Tree), which together with an auxiliary run-length representation of the model avoids visiting unselected surfaces and internal regions during a traversal of the model.Postprint (published version

Fast Reliable Ray-tracing of Procedurally Defined Implicit Surfaces Using Revised Affine Arithmetic

Fast and reliable rendering of implicit surfaces is an important area in the field of implicit modelling. Direct rendering, namely ray-tracing, is shown to be a suitable technique for obtaining good-quality visualisations of implicit surfaces. We present a technique for reliable ray-tracing of arbitrary procedurally defined implicit surfaces by using a modification of Affine Arithmetic called Revised Affine Arithmetic. A wide range of procedurally defined implicit objects can be rendered using this technique including polynomial surfaces, constructive solids, pseudo-random objects, procedurally defined microstructures, and others. We compare our technique with other reliable techniques based on Interval and Affine Arithmetic to show that our technique provides the fastest, while still reliable, ray-surface intersections and ray-tracing. We also suggest possible modifications for the GPU implementation of this technique for real-time rendering of relatively simple implicit models and for near real-time for complex implicit models

A progressive refinement approach for the visualisation of implicit surfaces

Visualising implicit surfaces with the ray casting method is a slow procedure. The design cycle of a new implicit surface is, therefore, fraught with long latency times as a user must wait for the surface to be rendered before being able to decide what changes should be introduced in the next iteration. In this paper, we present an attempt at reducing the design cycle of an implicit surface modeler by introducing a progressive refinement rendering approach to the visualisation of implicit surfaces. This progressive refinement renderer provides a quick previewing facility. It first displays a low quality estimate of what the final rendering is going to be and, as the computation progresses, increases the quality of this estimate at a steady rate. The progressive refinement algorithm is based on the adaptive subdivision of the viewing frustrum into smaller cells. An estimate for the variation of the implicit function inside each cell is obtained with an affine arithmetic range estimation technique. Overall, we show that our progressive refinement approach not only provides the user with visual feedback as the rendering advances but is also capable of completing the image faster than a conventional implicit surface rendering algorithm based on ray casting

Shell Multitasking

A system for switching among 2D application views or showing multiple windows for different applications at a same time on android in a virtual reality environment is disclosed. The applications render into one or more surfaces using layers, wherein the surfaces are managed by an out-of-process compositor. The layers are means of defining rendering for each of the surfaces during a time warp, which can produce a higher quality and performance of a rendered output. The time warp is a technique that warps a rendered image before sending it to a display. The rendered image is warped in order to make corrections for a head movement that occurs after it is rendered to the surfaces. While rendering to the surfaces, the applications configure the surfaces (as it may require) using various commands. While rendering from each of the applications, a “Surfaces” class and a “SurfaceTextures” class in android are utilized for a cross-process composition. The cross-process composition is a process in which a production of graphics occurs on one thread/process, and a consumption occurs from another thread/process. Further, a cross process layer (called as a VR system service or a VR runtime service) facilitates smooth switching of both rendering of an information and a systemUX (for example, a keyboard, a taskbar, dialogs, notifications, etc.) among the applications. Finally, the out-of-processor utilizes an internal API such as a SubmitFrame API to access all the layers, thus enabling the out-of-process compositor to perform a multi-surface and multi-application rendering. This way, by means of the out-of-process compositor, the multi-surface and multi-application rendering allows the multiple windows for different applications to be shown at a same time

Progressive refinement rendering of implicit surfaces

The visualisation of implicit surfaces can be an inefficient task when such surfaces are complex and highly detailed. Visualising a surface by first converting it to a polygon mesh may lead to an excessive polygon count. Visualising a surface by direct ray casting is often a slow procedure. In this paper we present a progressive refinement renderer for implicit surfaces that are Lipschitz continuous. The renderer first displays a low resolution estimate of what the final image is going to be and, as the computation progresses, increases the quality of this estimate at an interactive frame rate. This renderer provides a quick previewing facility that significantly reduces the design cycle of a new and complex implicit surface. The renderer is also capable of completing an image faster than a conventional implicit surface rendering algorithm based on ray casting

NeuralUDF: Learning Unsigned Distance Fields for Multi-view Reconstruction of Surfaces with Arbitrary Topologies

We present a novel method, called NeuralUDF, for reconstructing surfaces with arbitrary topologies from 2D images via volume rendering. Recent advances in neural rendering based reconstruction have achieved compelling results. However, these methods are limited to objects with closed surfaces since they adopt Signed Distance Function (SDF) as surface representation which requires the target shape to be divided into inside and outside. In this paper, we propose to represent surfaces as the Unsigned Distance Function (UDF) and develop a new volume rendering scheme to learn the neural UDF representation. Specifically, a new density function that correlates the property of UDF with the volume rendering scheme is introduced for robust optimization of the UDF fields. Experiments on the DTU and DeepFashion3D datasets show that our method not only enables high-quality reconstruction of non-closed shapes with complex typologies, but also achieves comparable performance to the SDF based methods on the reconstruction of closed surfaces.Comment: Visit our project page at https://www.xxlong.site/NeuralUDF