for opaque surfaces

This paper describes a new passive approach to capture time-varying scene geometry in large acquisition volumes from multi-view video. It can be applied to reconstruct complete moving models of human actors that feature even slightest dynamic geometry detail, such as wrinkles and folds in clothing, and that can be viewed from 360 ◦. Starting from multi-view video streams recorded under calibrated lighting, we first perform marker-less human motion capture based on a smooth template with no highfrequency surface detail. Subsequently, surface reflectance and time-varying normal fields are estimated based on the coarse template shape. The main contribution of this paper is a new statistical approach to solve the non-trivial problem of transforming the captured normal field that is defined over the smooth non-planar 3D template into true 3D displacements. Our spatio-temporal reconstruction method outputs displaced geometry that is accurate at each time step of video and temporally smooth, even if the input data are affected by noise.

Abstract: The importance of landscape and heritage recording and documentation with optical remote sensing sensors is well recognized at international level. The continuous development of new sensors, data capture methodologies and multi-resolution 3D representations, contributes significantly to the digital 3D documentation, mapping, conservation and representation of landscapes and heritages and to the growth of research in this field. This article reviews the actual optical 3D measurement sensors and 3D modeling techniques, with their limitations and potentialities, requirements and specifications. Examples of 3D surveying and modeling of heritage sites and objects are also shown throughout the paper.

This state of the art report covers reconstruction methods for transparent and specular objects or phenomena. While the 3D acquisition of opaque surfaces with lambertian reflectance is a well-studied problem, transparent, refractive, specular and potentially dynamic scenes pose challenging problems for acquisition systems. This report reviews and categorizes the literature in this field. Despite tremendous interest in object digitization, the acquisition of digital models of transparent or specular objects is far from being a solved problem. On the other hand, real-world data is in high demand for applications such as object modeling, preservation of historic artifacts and as input to data driven modeling techniques. With this report we aim at providing a reference for and an introduction to the field of transparent and specular object reconstruction. We describe acquisition approaches for different classes of objects. Transparent objects/phenomena that do not change the straight ray geometry can be found foremost in natural phenomena. Refraction effects are usually small and can be considered negligible for these objects. Phenomena as diverse as fire, smoke, and interstellar nebulae can be modeled using a straight ray model of image formation. Refractive and specular surfaces on the other hand change the straight rays into usually piecewise linear ray paths, adding additional complexity to the reconstruction problem. Translucent objects exhibit significant sub-surface scattering effects rendering traditional acquisition approaches unstable. Different classes of techniques have been developed to deal with these problems and good reconstruction results can be achieved with current state-of-the-art techniques. However, the approaches are still specialized and targeted at very specific object classes. We classify the existing literature and hope to provide an entry point to this exiting field.

This paper reviews the latest developments of displacement mapping algorithms implemented on the vertex, geometry, and fragment shaders of graphics cards. Displacement mapping algorithms are classified as per-vertex and per-pixel methods. Per-pixel approaches are further categorized as safe algorithms that aim at correct solutions in all cases, to unsafe techniques that may fail in extreme cases but are usually much faster than safe algorithms, and to combined methods that exploit the robustness of safe and the speed of unsafe techniques. We discuss the possible roles of vertex, geometry, and fragment shaders to implement these algorithms. Then the particular GPU based bump, parallax, relief, sphere, horizon mapping, cone stepping, local ray tracing, pyramidal and view-dependent displacement mapping methods, as well as their numerous variations are reviewed providing also implementation details of the shader programs. We present these methods using uniform notations and also point out when different authors called similar concepts differently. In addition to basic displacement mapping, self-shadowing and silhouette processing are also reviewed. Based on our experiences gained having re-implemented these methods, their performance and quality are compared, and the advantages and disadvantages are fairly presented.

Algorithms for scene understanding and realistic image synthesis require accurate models of the way real-world materials scatter light. This class describes recent work in the graphics community to measure the spatially- and directionally-varying reflectance and subsurface scattering of complex materials, and to develop efficient representations and analysis tools for these datasets. We describe the design of acquisition devices and capture strategies for BRDFs and BSSRDFs, efficient factored representations, and a case study of capturing the appearance of human faces.

Interesting textures form on the surfaces of objects as the result of external chemical, mechanical, and biological agents. Simulating these textures is necessary to generate models for realistic image synthesis. The textures formed are progressively variant, with the variations depending on the global and local geometric context. We present a method for capturing progressively varying textures and the relevant context parameters that control them. By relating textures and context parameters, we are able to transfer the textures to novel synthetic objects. We present examples of capturing chemical effects, such as rusting; mechanical effects, such as paint cracking; and biological effects, such as the growth of mold on a surface. We demonstrate a user interface that provides a method for specifying where an object is exposed to external agents. We show the results of complex, geometry-dependent textures evolving on synthetic objects.

This state of the art report covers reconstruction methods for transparent and specular objects or phenomena. While the 3D acquisition of opaque surfaces with lambertian reflectance is a well-studied problem, transparent, refractive, specular and potentially dynamic scenes pose challenging problems for acquisition systems. This report reviews and categorizes the literature in this field. Despite tremendous interest in object digitization, the acquisition of digital models of transparent or specular objects is far from being a solved problem. On the other hand, real-world data is in high demand for applications such as object modeling, preservation of historic artifacts and as input to data-driven modeling techniques. With this report we aim at providing a reference for and an introduction to the field of transparent and specular object reconstruction. We describe acquisition approaches for different classes of objects. Transparent objects/phenomena that do not change the straight ray geometry can be found foremost in natural phenomena. Refraction effects are usually small and can be considered negligible for these objects. Phenomena as diverse as fire, smoke, and interstellar nebulae can be modeled using a straight ray model of image formation. Refractive and specular surfaces on the other hand change the straight rays into usually piecewise linear ray paths, adding additional complexity to the reconstruction problem. Translucent objects exhibit significant sub-surface scattering effects rendering traditional acquisition approaches unstable. Different classes of techniques have been developed to deal with these problems and good reconstruction results can be achieved with current state-of-the-art techniques. However, the approaches are still specialized and targeted at very specific object classes. We classify the existing literature and hope to provide an entry point to this exiting field.

Figure 1: Renderings of high-resolution SVBRDFs reconstructed by our method from two-phase, low-dimensional captured data. (a) Anisotropic brushed

Most illuminant estimation algorithms work with the assumption of one specific type of the light source (e.g. point light source or directional light source). This assumption brings up two main limitations which significantly restrict the applicability of the algorithms: First, the knowledge about the type of the light source presented in the scene is needed a priori; second, it can not handle complex scenes where multiple different types of light sources co-exist. To overcome these limitations, we remove the assumption about the source type and develop a general light source model for all different types of light sources. Based on this general light source model, we propose a unified framework to estimate multiple illuminants of different types. Within the framework, we use an experiment setup where a calibration sphere with a specular surface is utilized to probe the scene illuminants and a novel ray tracing and matching algorithm is devised to estimate the light source parameters. Experiment results demonstrate the accuracy of our method on a variety of real images. 1