Reflectance Analysis for 3D Computer Graphics Model Generation

In augmented virtuality, estimating object surface reflectance properties is important when rendering objects under arbitrary illumination conditions. However, faithfully estimating surface reflectance properties is difficult for objects having interreflections. The present paper describes a new method for densely estimating the non-uniform surface reflectance properties of real objects constructed of convex and concave surfaces having diffuse and specular interreflections. The registered range and surface color texture images were obtained using a laser rangefinder. In the proposed method, the light positions are first determined in order to take color images, which are then used to discriminate diffuse and specular reflection components of surface reflection. Surface reflectance parameters are then estimated based on an inverse global illumination rendering. Experiments were conducted to reveal the usefulness of the proposed method.

An object model for computer graphics applications should contain two aspects of information: shape and reflectance properties of the object. A number of techniques have been developed for modeling object shapes by observing real objects. In contrast, attempts to model reflectance properties of real objects have been rather limited. In most cases, modeled reflectance properties are too simple or too complicated to be used for synthesizing realistic images of the object.In this paper, we propose a new method for modeling object reflectance properties, as well as object shapes, by observing real objects. First, an object surface shape is reconstructed by merging multiple range images of the object. By using the reconstructed object shape and a sequence of color images of the object, parameters of a reflection model are estimated in a robust manner. The recovered object shape and reflectance properties are then used for synthesizing object images with realistic shading effects under arbitrary illumination conditions.KeywordsTriangular MeshSpecular ReflectionRange ImageObject ShapeObject SurfaceThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Computer vision systems can be used to determine the shapes of real three-dimensional objects for purposes of object recognition and pose estimation or for CAD applications. One method that has been developed is photometric stereo. This method uses several images taken from the same viewpoint, but with different lightings, to determine the three-dimensional shape of an object. Most previous work in photometric stereo has been with gray-tone images; color images have only been used for dielectric materials. In this paper we describe a procedure for color photometric stereo, which recovers the shape of a colored object from two or more color images of the object under white illumination. This method can handle different types of materials, such as composites and metals, and can employ various reflection models such as the Lambertian, dichromatic, and Torrance-Sparrow models. For composite materials, colored metals, and dielectrics, there are two advantages of utilizing color information: at each pixel, there are more constraints on the orientation, and the result is less sensitive to noise. Consequently, the shape can be found more accurately. The method has been tested on both artificial and real images of objects of various materials, and on real images of a multi-colored object.

Separating specular reflection components from diffuse reflection components is an important subject in computer vision. Hence, the author's group has developed a method to separate a diffuse image from a high-speed-video image with specular reflection components. The method uses an estimation technique based on luminance variation owing to flicker of a strobe. However, an issue with the method is that the strobe produces a new specular reflection component. In this study, we get around this limitation by introducing a method for combining two images produced based on flickering information. Experimental results show the validity of the proposed method.

The problem of estimating an illumination distribution from images is called inverse lighting. For inverse lighting, three approaches have been developed based on specular reflection components, diffuse reflection components, and cast shadows. The present study provides theoretical insights as to why the approach based on cast shadows works in a reliable manner, and discusses what kind of basis functions are appropriate to be used for recovering illumination from cast shadows. First, we formalize the approach based on cast shadows by using spherical harmonics. Then, we analyze the approach in the frequency domain and show the advantages and the limitations of the approach. Second, motivated by the observations in the frequency domain, we propose an efficient method using Haar wavelets that provide compact supports and sparsity of coefficients. Finally, we report the results of experiments that compared the method using spherical harmonics and the method using Haar wavelets.

The present paper proposes a method for estimating various parameters of a reflection model from a single color image measured with a camera. The dichromatic reflection model of the Phong type is used for an inhomogeneous dielectric object. The object's shape is assumed to be cylindrical. First we analyze a relationship between the reflection properties of a cylinder object and the color histogram. Second, Algorithms are developed for estimating several parameters of (1) object color vector, (2) illumination direction, (3) illumination color vector, (4) surface roughness, and (5) ratio of interface to body intensity. Finally the feasibility of the proposed method is shown in an experiment.KeywordsColor HistogramReflection PropertyObject ColorReflection ModelIllumination DirectionThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Several techniques have been developed for recovering reflectance properties of real surfaces under unknown illumination conditions. However, in most cases, those techniques assume that the light sources are located at infinity, which cannot be applied to, for example, photometric modelling of indoor environments. We propose two methods to estimate the surface reflectance property of an object, as well as the position of a light source from a single image without the distant illumination assumption. Given a color image of an object with specular reflection as an input, the first method estimates the light source position by fitting to the Lambertian diffuse component, while separating the specular and diffuse components by using an iterative relaxation scheme. Moreover, we extend the above method by using a single specular image as an input, thus removing its constraints on the diffuse reflectance property and the number of light sources. This method simultaneously recovers the reflectance properties and the light source positions by optimizing the linearity of a log-transformed Torrance-Sparrow model. By estimating the object's reflectance property and the light source position, we can freely generate synthetic images of the target object under arbitrary source directions and source-surface distances.

The diffuse and specular components of leaf reflection are both important to determine the leaf optical properties as well as to describe the leaf bidirectional reflectance distribution function (BRDF). However, the specular component is usually ignored in practice in numerous canopy reflectance models that describe the interaction between solar light and vegetated scene components. To evaluate the impact of leaf-specular reflection on canopy bidirectional reflectance factor (BRF) characteristics, we introduce a leaf BRDF model into the radiosity-graphics combined model (RGM; a 3-D scene model) to calculate canopy BRFs with nondiffuse leaves. The modified RGM is validated by comparing simulated BRFs against in situ measured BRFs over real maize canopies. The results show that ignorance of leaf-specular reflection can result in up to 50% of relative error in the blue band (435.8 nm). A series of maize canopies with different leaf angle distributions (LADs) is reconstructed to investigate the effect of five major biophysical/geometrical parameters such as leaf area index, LAD, leaf surface property, view direction, and solar zenith angle on leaf-specular reflection contributions to the canopy BRF. It is demonstrated that increasing the incident solar zenith angle and decreasing the mean leaf angle impact the angular distribution of the canopy BRF more significantly than other factors. The cumulative hemispherical relative and absolute errors of canopy BRF caused by the leaf-specular reflection are often too large to be ignored, even for canopies with rough surface leaves. Moreover, the relative error of BRF in visible waveband shows that, in general, leaf-specular reflection has a large impact than that in near-infrared waveband. However, such impact can be sufficiently accounted for by even just consideration of the first-order leaf-specular reflection in canopy reflectance calculation, leading to a substantial improvement in simulation accuracy for most vegetation canopies.

PROBA-V mission was conceived, and launched by ESA in 2013, to ensure continuity to the SPOT - VGT longterm data series of global daily land observations, started in 1998, bridging the gap to Sentinel-3. Nowadays, thanks to the successful and smooth operations of the PROBA- V satellite, a >20 years consistent data record of land surface reflectances, is available to the scientific community. This long-term dataset has clear relevance for trend analysis, anomaly detection and climate related applications. Despite this obvious interest, the exploitation of this dataset is still limited and mostly focused to near-real time applications, using the SPOT - VGT archive as a background average to detect anomalies, e.g., in NDVI time series. In order to fill this gap, and to exploit the full potential of this dataset, ESA has funded a new project called CISAR@MEP, whose primary goal is to set the stage for the generation of a global 20 years long-term data record of surface reflectance and aerosol properties from analysis of SPOT-VGT and PROBA-V observations. For this purpose, a recently developed algorithm, called CISAR and developed by Rayference, will be used, allowing the joint retrieval of aerosol and surface reflectance properties, together with the associated retrieval uncertainties. This new long-term data record will eventually fulfill current Global Climate Observing System (GCOS) requirements for the generation of Essential Climate Variables (ECVs), such as surface albedo and aerosol optical thickness, being 5% and 10%, respectively. Such data set can support the needs of both the atmospheric and land surface research communities and it can contribute to Copernicus operational service and ESA Climate Change Initiatives (CCI) activities. The CISAR@MEP project started during Q1 2019 with expected 2 years duration. The aim of this paper is to present this ESA funded project, to illustrate the objectives and the methodology and to provide some preliminary results. Furthermore, the technological implementation approach will be detailed, which makes full use of the PROBA-V Mission Exploitation Platform (MEP), a scalable processing environment, providing direct access to both SPOT-VGT and PROBA-V full mission archive together with the required resources and tools.

A method is proposed for estimating spectral radiances of the surrounding scene from a reflected image on the corneal surface. A digital color camera and the human eyeball are used to develop a simple imaging system without any specific device. The corneal image consists of a mixture of specular and diffuse reflections from the cornea and the iris. The desired scene radiances are only recovered from the specular reflection component after removing the diffuse reflection component. Experiments are executed in several different conditions.

Estimation of hybrid reflectance properties and shape reconstruction using the LMS method

Combined heat transfer in floating zone growth of large silicon crystals with radiation on diffuse and specular surfaces

Among the major remaining challenges for generative adversarial networks (GANs) is the capacity to synthesize globally and locally coherent images with object shapes and textures indistinguishable from real images. To target this issue we propose an alternative U-Net based discriminator architecture, borrowing the insights from the segmentation literature. The proposed U-Net based architecture allows to provide detailed per-pixel feedback to the generator while maintaining the global coherence of synthesized images, by providing the global image feedback as well. Empowered by the per-pixel response of the discriminator, we further propose a per-pixel consistency regularization technique based on the CutMix data augmentation, encouraging the U-Net discriminator to focus more on semantic and structural changes between real and fake images. This improves the U-Net discriminator training, further enhancing the quality of generated samples. The novel discriminator improves over the state of the art in terms of the standard distribution and image quality metrics, enabling the generator to synthesize images with varying structure, appearance and levels of detail, maintaining global and local realism. Compared to the BigGAN baseline, we achieve an average improvement of 2.7 FID points across FFHQ, CelebA, and the proposed COCO-Animals dataset.

The purpose of the present study is to combine the two theories of Shabah al-Mohaki (the representative image), and Wojud al-Zehni (the mental existence). In the context of Islamic philosophy, the relationship between mental and external realities has been a controversial issue among philosophers. It is well known that proponents of Shabah al-Mohaki believe that there is a dissimilarity between mental and external realities, and their rivals, the proponents of mental existence, believe that there is an essential identity between mental and external realities. This group claims that objects have two types of existence; "objective" which is the same reality in the external world, and “subjective” which is called "mental existence". It seems that in their view, subjective and objective realities are numerically identical. The representative theorists on the other side reject this claim. By investigating and analyzing the texts of the two theories, the author found that the two speak of identity but qualitative and not numerical identity. As far as the mental existence theory is concerned, when we analyze the claim of mental existence theorists and numerical identity, it turns out that they do not say anything better and more than what representative theorists claim. This analysis is done through the two principles of indiscernibility of identicals and identity of indiscernibles. According to the first, if two things are identical then they must be not be different from one another with respect to all of their properties. The principle speaks of numerical identity. The second principle (although it is controversial) states that if two things have the same properties in every respect then they are identical. This principle does not have the logical truth and speaks of qualitative identity. If one considers the case of mental existence, the claim that mental existence and objective reality are numerically identical, then he identifies that these two are not only identical but they have different properties. For instance, the subjective reality such as the image of a book or fire has the property of being mental and the objective reality of that image, the book or fire in the external world, has the property of being external. This shows that they are two different things because they have different properties. Therefore, the only way to say that these two are the same (identical), is that they are qualitatively but not numerically, identical. On the other side, the identity claim (qualitative identity) between subjective and objective realities is found in the texts of proponents of representative theorists. For instance, Shamsuddin Isfahani argues that what is ascribed to mental existence is an image of objective reality and the image of that particular object is contrary to the objective reality itself, although in some respects it is identical to that external reality in such a way that what is obtained from the object in the mind is the same as the external reality. This shows that representative theorists also accept the claim of identity in some respect but qualitative and not numerical identity between subjective and objective reality.

Previous studies have found that preschoolers are confused about the relationship between two‐dimensional (2D) symbols and their referents. Preschoolers report that 2D images (e.g. televised images and photographs) share some of the characteristics of the objects they are representing. A novel Comparison Task was created to test what might account for these misattributions of the properties of 2D images. Three‐and‐a‐half‐ and four‐and‐a‐half‐year olds made comparisons between items presented in two of three formats simultaneously, i.e. as a real object and as an object appearing on television (TV), as a real object and as a photo of that object, or as an object appearing on TV and in a photo. Presenting the televised object or the photo of the object along with the real object aided performance; children indicated that televised objects and photos of objects no longer shared the properties of the real objects. Children also performed better when presented with two 2D images of the same object (the photo of the object and the televised image of the object). Although dual‐representation might account for these misattributions of the properties of 2D images, because children also performed better when two 2D images of the same object were present, other possibilities such as children using pictures as communicative devices and disregarding the pragmatics of the task should be explored. Copyright © 2010 John Wiley & Sons, Ltd.