Single-shot layered reflectance separation using a polarized light field camera

We present a novel computational photography technique for single shot separation of diffuse/specular reflectance as well as novel angular domain separation of layered reflectance. Our solution consists of a two-way polarized light field (TPLF) camera which simultaneously captures two orthogonal states of polarization. A single photograph of a subject acquired with the TPLF camera under polarized illumination then enables standard separation of diffuse (depolarizing) and polarization preserving specular reflectance using light field sampling. We further demonstrate that the acquired data also enables novel angular separation of layered reflectance including separation of specular reflectance and single scattering in the polarization preserving component, and separation of shallow scattering from deep scattering in the depolarizing component. We apply our approach for efficient acquisition of facial reflectance including diffuse and specular normal maps, and novel separation of photometric normals into layered reflectance normals for layered facial renderings. We demonstrate our proposed single shot layered reflectance separation to be comparable to an existing multi-shot technique that relies on structured lighting while achieving separation results under a variety of illumination conditions

Analysis of Human Faces Using a Measurement-Based Skin Reflectance Model

We have measured 3D face geometry, skin reflectance, and subsurface scattering using custom-built devices for 149 subjects of varying age, gender, and race. We developed a novel skin reflectance model whose parameters can be estimated from measurements. The model decomposes the large amount of measured skin data into a spatially-varying analytic BRDF, a diffuse albedo map, and diffuse subsurface scattering. Our model is intuitive, physically plausible, and -- since we do not use the original measured data -- easy to edit as well. High-quality renderings come close to reproducing real photographs. The analysis of the model parameters for our sample population reveals variations according to subject age, gender, skin type, and external factors (e.g., sweat, cold, or makeup). Using our statistics, a user can edit the overall appearance of a face (e.g., changing skin type and age) or change small-scale features using texture synthesis (e.g., adding moles and freckles). We are making the collected statistics publicly available to the research community for applications in face synthesis and analysis.Engineering and Applied Science

Rendering human skin using a multi-layer reflection model

A key element to creating realistic images is the appearance of surfaces. In order to overcome the artificial look of synthetic humans, human skin has to be modelled in all its variety. A new physically-based skin reflection model is presented in this paper to render a diverse selection of skin complexions. The reflection model is based on steady-state light transport theory in multi-layered skin tissue. A three-layer simulation model has been developed to capture the effect of natural sebum on skin appearance. Sebum is found over most parts of the body, causing skin to look more specular, depending on the viewing conditions. Optical and geometric properties are used as control parameters to influence the surface reflection and subsurface scattering of light within the three layers. The resultant reflection consists of the specular reflection due to the Fresnel effect, as well as the diffuse reflection from subsurface scattering. The Monte Carlo method isused to simulate the propagation of light in skin tissue. Various effects like scattering, absorption, reflection and transmission have been taken into account. The bi-directional reflectance distribution function (BRDF) obtained from the simulation is used to render the appearance of human skin. Comparisons between the simulated BRDF results and experimental measurements show that the physical simulation is highly realistic

An Introduction to Light Interaction with Human Skin

Despite the notable progress in physically-based rendering, there is still a long way to go before one can automatically generate predictable images of organic materials such as human skin. In this tutorial, the main physical and biological aspects involved in the processes of propagation and absorption of light by skin tissues are examined. These processes affect not only skin appearance, but also its health. For this reason, they have also been the object of study in biomedical research. The models of light interaction with human skin developed by the biomedical community are mainly aimed at the simulation of skin spectral properties which are used to determine the concentration and distribution of various substances. In computer graphics, the focus has been on the simulation of light scattering properties that affect skin appearance. Computer models used to simulate these spectral and scattering properties are described in this tutorial, and their strengths and limitations discussed. Keywords: natural phenomena, biologically and physically-based rendering

Practical Measurement and Reconstruction of Spectral Skin Reflectance

We present two practical methods for measurement of spectral skin reflectance suited for live subjects, and drive a spectral BSSRDF model with appropriate complexity to match skin appearance in photographs, including human faces. Our primary measurement method employs illuminating a subject with two complementary uniform spectral illumination conditions using a multispectral LED sphere to estimate spatially varying parameters of chromophore concentrations including melanin and hemoglobin concentration, melanin blend-type fraction, and epidermal hemoglobin fraction. We demonstrate that our proposed complementary measurements enable higher-quality estimate of chromophores than those obtained using standard broadband illumination, while being suitable for integration with multiview facial capture using regular color cameras. Besides novel optimal measurements under controlled illumination, we also demonstrate how to adapt practical skin patch measurements using a hand-held dermatological skin measurement device, a Miravex Antera 3D camera, for skin appearance reconstruction and rendering. Furthermore, we introduce a novel approach for parameter estimation given the measurements using neural networks which is significantly faster than a lookup table search and avoids parameter quantization. We demonstrate high quality matches of skin appearance with photographs for a variety of skin types with our proposed practical measurement procedures, including photorealistic spectral reproduction and renderings of facial appearance

DMD-based software-configurable spatially-offset Raman spectroscopy for spectral depth-profiling of optically turbid samples

Spectral depth-profiling of optically turbid samples is of high interest to a broad range of applications. We present a method for measuring spatially-offset Raman spectroscopy (SORS) over a range of length scales by incorporating a digital micro-mirror device (DMD) into a sample-conjugate plane in the detection optical path. The DMD can be arbitrarily programmed to collect/reject light at spatial positions in the 2D sample-conjugate plane, allowing spatially offset Raman measurements. We demonstrate several detection geometries, including annular and simultaneous multi-offset modalities, for both macro- and micro-SORS measurements, all on the same instrument. Compared to other SORS modalities, DMD-based SORS provides more flexibility with only minimal additional experimental complexity for subsurface Raman collection

BSSRDF estimation from single images

We present a novel method to estimate an approximation of the reflectance characteristics of optically thick, homogeneous translucent materials using only a single photograph as input. First, we approximate the diffusion profile as a linear combination of piecewise constant functions, an approach that enables a linear system minimization and maximizes robustness in the presence of suboptimal input data inferred from the image. We then fit to a smoother monotonically decreasing model, ensuring continuity on its first derivative. We show the feasibility of our approach and validate it in controlled environments, comparing well against physical measurements from previous works. Next, we explore the performance of our method in uncontrolled scenarios, where neither lighting nor geometry are known. We show that these can be roughly approximated from the corresponding image by making two simple assumptions: that the object is lit by a distant light source and that it is globally convex, allowing us to capture the visual appearance of the photographed material. Compared with previous works, our technique offers an attractive balance between visual accuracy and ease of use, allowing its use in a wide range of scenarios including off-the-shelf, single images, thus extending the current repertoire of real-world data acquisition techniques

Pushing the Limits of 3D Color Printing: Error Diffusion with Translucent Materials

Accurate color reproduction is important in many applications of 3D printing, from design prototypes to 3D color copies or portraits. Although full color is available via other technologies, multi-jet printers have greater potential for graphical 3D printing, in terms of reproducing complex appearance properties. However, to date these printers cannot produce full color, and doing so poses substantial technical challenges, from the shear amount of data to the translucency of the available color materials. In this paper, we propose an error diffusion halftoning approach to achieve full color with multi-jet printers, which operates on multiple isosurfaces or layers within the object. We propose a novel traversal algorithm for voxel surfaces, which allows the transfer of existing error diffusion algorithms from 2D printing. The resulting prints faithfully reproduce colors, color gradients and fine-scale details.Comment: 15 pages, 14 figures; includes supplemental figure

The use of Frequency domain Electro-magnetometer for the characterization of permafrost and ice layers.

openSince the industrial revolution human activities caused a record-breaking increase in the Earth’s average temperature due to the extensive use of greenhouse gases. [1] As global temperatures increase; glaciers have undergone a significant retreat in the past few decades.[2] The Ice Memory project aims to preserve ice cores from glaciers worldwide, as a record of Earth's past climate. It involves drilling deep into glaciers, extracting ice cores, and storing them in a dedicated facility in Antarctica. This is to prevent the potential loss of valuable climate archives due to glacier retreat which provides future scientists with valuable information for studying historical climate patterns and understanding the role of human activity in climate change. geophysical investigations are typically required to determine the most suitable drilling positions for ice coring. the most common technique for this purpose is the so-called GPR. (Snow cover of several meters limits the use of ERT and active seismic methods.) While each geophysical technique has certain advantages and limitations, combining them can provide a more detailed picture of changes within rock glaciers. In the present study, electromagnetic prospecting in the frequency domain (FDEM) was performed together with the ground penetration radar (GPR). The former is not a commonly used method for studying glacier environments as FDEM has a lower resolution in the study of glaciers with respect to the GPR. However, as we will see in this study, it is a quick and convenient method to study this type of environment, as it provides a large coverage area in a cost-efficient manner, although with a lower resolution with respect to the GPR. Combining these two techniques provide a more detailed map of the glaciers. comparing the GPR and borehole data with the inverted FDEM datasets (CMD-DUO, GF-Instruments) confirms the effectiveness and applicability of FDEM methodology for investigating glacial bodies in mountainous regions.Since the industrial revolution human activities caused a record-breaking increase in the Earth’s average temperature due to the extensive use of greenhouse gases. [1] As global temperatures increase; glaciers have undergone a significant retreat in the past few decades.[2] The Ice Memory project aims to preserve ice cores from glaciers worldwide, as a record of Earth's past climate. It involves drilling deep into glaciers, extracting ice cores, and storing them in a dedicated facility in Antarctica. This is to prevent the potential loss of valuable climate archives due to glacier retreat which provides future scientists with valuable information for studying historical climate patterns and understanding the role of human activity in climate change. geophysical investigations are typically required to determine the most suitable drilling positions for ice coring. the most common technique for this purpose is the so-called GPR. (Snow cover of several meters limits the use of ERT and active seismic methods.) While each geophysical technique has certain advantages and limitations, combining them can provide a more detailed picture of changes within rock glaciers. In the present study, electromagnetic prospecting in the frequency domain (FDEM) was performed together with the ground penetration radar (GPR). The former is not a commonly used method for studying glacier environments as FDEM has a lower resolution in the study of glaciers with respect to the GPR. However, as we will see in this study, it is a quick and convenient method to study this type of environment, as it provides a large coverage area in a cost-efficient manner, although with a lower resolution with respect to the GPR. Combining these two techniques provide a more detailed map of the glaciers. comparing the GPR and borehole data with the inverted FDEM datasets (CMD-DUO, GF-Instruments) confirms the effectiveness and applicability of FDEM methodology for investigating glacial bodies in mountainous regions