Photorealistic Renderings Research Articles

Acquisition and Validation of Spectral Ground Truth Data for Predictive Rendering of Rough Surfaces

AbstractPhysically based rendering uses principles of physics to model the interaction of light with matter. Even though it is possible to achieve photorealistic renderings, it often fails to be predictive. There are two major issues: first, there is no analytic material model that considers all appearance critical characteristics; second, light is in many cases described by only 3 RGB‐samples. This leads to the problem that there are different models for different material types and that wavelength dependent phenomena are only approximated. In order to be able to analyze the influence of both problems on the appearance of real world materials, an accurate comparison between rendering and reality is necessary. Therefore, in this work, we acquired a set of precisely and spectrally resolved ground truth data. It consists of the precise description of a new developed reference scene including isotropic BRDFs of 24 color patches, as well as the reference measurements of all patches under 13 different angles inside the reference scene. Our reference data covers rough materials with many different spectral distributions and various illumination situations, from direct light to indirect light dominated situations.

Point-based rendering enhancement via deep learning

Current state-of-the-art point rendering techniques such as splat rendering generally require very high-resolution point clouds in order to create high-quality photo realistic renderings. These can be very time consuming to acquire and oftentimes also require high-end expensive scanners. This paper proposes a novel deep learning-based approach that can generate high-resolution photo realistic point renderings from low-resolution point clouds. More specifically, we propose to use co-registered high-quality photographs as the ground truth data to train the deep neural network for point-based rendering. The proposed method can generate high-quality point rendering images very efficiently and can be used for interactive navigation of large-scale 3D scenes as well as image-based localization. Extensive quantitative evaluations on both synthetic and real datasets show that the proposed method outperforms state-of-the-art methods.

Does the type of presentation medium impact assessments of the built environment? An examination of environmental usability ratings across three modes of presentation

A literature review confirms that evaluations of and responses to an environment are similar whether the presentation medium is the physical environment; a photograph of it; or a dynamic, virtual reality simulation. However, studies have not been conducted to determine if photorealistic renderings would receive similar assessments as a physical space or photograph. Accordingly, this work aimed to determine if prospective environmental usability assessments differ across presentation media. Participants viewed one of two built environments by either standing in the physical space, examining a photograph of it, or looking at a rendering of it. Participants then assessed the prospective usability of the space. The findings revealed that overall presentation media had little to no impact on the environmental assessments—meaning static, simulated images of the built environment can be used in evaluations. These findings are applicable to fields like architecture, which use renderings to communicate designs for future spaces.

An Efficient Scan Conversion of Parabola on Hexagonal Grid

In this paper the midpoint approach for efficient scan conversion of parabola on hexagonal grid is proposed. The mid-point approach computes pixel nearest true curve using only integer arithmetic. The proposed algorithm is compared favorably with the existing parabola drawing algorithm on square grid. Owing to this approach we may visualize design ideas through animations and photorealistic renderings, and simulate how a design will perform in the real world in CAD tool with less aliasing artifact.

Unified Boundary-Aware Texturing for Interactive Volume Rendering

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.

Automatic 3D shape recovery for rapid prototyping

The capacity to create, display and manipulate a three-dimensional (3D) computer model and produce a physical replica of an existing object, enabling 3D re-shaping activities, plays an important role in different areas such as engineering, biology, architecture and archaeology. Some improvements have been made in a biologically based computer-aided design system, called BioCAD, specifically designed for the rapid and accurate 3D shape recovery from existing large objects, creating 3D computer models either to produce sophisticated photo-realistic renderings, two-dimensional drawings, or to generate surface models for simulation purposes and rapid prototyping applications. This improved system comprises three main routines through which the major findings are as follows: i) the algorithm for “ciliary” calibration routine enables to converge all digital image sequence, so uncertainties decrease, resulting in higher accuracy; ii) through the binocular stereopsis routine, the 3D shape of the perceived large object can actually be inferred; iii) STL and SLI routine allows to integrate BioCAD system and other advanced computer-aided technologies, enabling one to obtain a very small layer thickness from a straightforward slicing process of STL files with a large dimension, minimising the slicing processing time by exploring the advantage of the Matlab language, in terms of matrix manipulation and RAM memory of personal computers.

Acquisition, Synthesis, and Rendering of Bidirectional Texture Functions

Abstract One of the main challenges in computer graphics is still the realistic rendering of complex materials such as fabric or skin. The difficulty arises from the complex meso structure and reflectance behavior defining the unique look‐and‐feel of a material. A wide class of such realistic materials can be described as 2D‐texture under varying light‐ and view direction, namely, the Bidirectional Texture Function (BTF). Since an easy and general method for modeling BTFs is not available, current research concentrates on image‐based methods, which rely on measured BTFs (acquired real‐world data) in combination with appropriate synthesis methods. Recent results have shown that this approach greatly improves the visual quality of rendered surfaces and therefore the quality of applications such as virtual prototyping. This state‐of‐the‐art report (STAR) will present the techniques for the main tasks involved in producing photo‐realistic renderings using measured BTFs in details.

Computer rapid design I: accuracy analysis

A new biologically based CAD tool (BioCAD), based on a hybrid modelling approach, was developed for the rapid generation of computer models from existing large objects. This hybrid method uses the more appropriated algorithms and procedures from both photogrammetry and computer vision in combination with biologically based algorithms replicating the human vision process into a computer programme. This BioCAD system, designed to automatically produce high-quality models, uses two-dimensional (2D) photos to create three-dimensional (3D) computer models, either to produce sophisticated photo-realistic renderings, 2D drawings, or to generate surface models for simulation purposes and rapid prototyping applications. To achieve accurate results on the 3D computer models, all the error sources must be analysed. The calibration procedure is crucial, as errors arising from this first process will have a great impact on the 3D model. A detailed distortion analysis of digital images for BioCAD is performed in order to achieve a higher accuracy of results through a novel and automatic calibration procedure called ciliary.