DeLight-Net: Decomposing Reflectance Maps into Specular Materials and Natural Illumination

In this paper we are extracting surface reflectance and natural environmental illumination from a reflectance map, i.e. from a single 2D image of a sphere of one material under one illumination. This is a notoriously difficult problem, yet key to various re-rendering applications. With the recent advances in estimating reflectance maps from 2D images their further decomposition has become increasingly relevant. To this end, we propose a Convolutional Neural Network (CNN) architecture to reconstruct both material parameters (i.e. Phong) as well as illumination (i.e. high-resolution spherical illumination maps), that is solely trained on synthetic data. We demonstrate that decomposition of synthetic as well as real photographs of reflectance maps, both in High Dynamic Range (HDR), and, for the first time, on Low Dynamic Range (LDR) as well. Results are compared to previous approaches quantitatively as well as qualitatively in terms of re-renderings where illumination, material, view or shape are changed.Comment: Stamatios Georgoulis and Konstantinos Rematas contributed equally to this wor

A general illumination model for molecular visualization

Several visual representations have been developed over the years to visualize molecular structures, and to enable a better understanding of their underlying chemical processes. Today, the most frequently used atom-based representations are the Space-filling, the Solvent Excluded Surface, the Balls-and-Sticks, and the Licorice models. While each of these representations has its individual benefits, when applied to large-scale models spatial arrangements can be difficult to interpret when employing current visualization techniques. In the past it has been shown that global illumination techniques improve the perception of molecular visualizations; unfortunately existing approaches are tailored towards a single visual representation. We propose a general illumination model for molecular visualization that is valid for different representations. With our illumination model, it becomes possible, for the first time, to achieve consistent illumination among all atom-based molecular representations. The proposed model can be further evaluated in real-time, as it employs an analytical solution to simulate diffuse light interactions between objects. To be able to derive such a solution for the rather complicated and diverse visual representations, we propose the use of regression analysis together with adapted parameter sampling strategies as well as shape parametrization guided sampling, which are applied to the geometric building blocks of the targeted visual representations. We will discuss the proposed sampling strategies, the derived illumination model, and demonstrate its capabilities when visualizing several dynamic molecules.Peer ReviewedPostprint (author's final draft

Helium line formation and abundance during a C-class flare

During a coordinated campaign which took place in May 2001, a C-class flare was observed both with SOHO instruments and with the Dunn Solar Telescope of the National Solar Observatory at Sacramento Peak. In two previous papers we have described the observations and discussed some dynamical aspects of the earlier phases of the flare, as well as the helium line formation in the active region prior to the event. Here we extend the analysis of the helium line formation to the later phases of the flare in two different locations of the flaring area. We have devised a new technique, exploiting all available information from various SOHO instruments, to determine the spectral distribution of the photoionizing EUV radiation produced by the corona overlying the two target regions. In order to find semiempirical models matching all of our observables, we analyzed the effect on the calculated helium spectrum both of A(He) (the He abundance) and of the uncertainties in the incident EUV radiation (level and spectral distribution). We found that the abundance has in most cases (but not in all) a larger effect than the coronal back-radiation. The result of our analysis is that, considering the error of the measured lines, and adopting our best estimate for the coronal EUV illumination, the value A(He)=0.075 +/- 0.010 in the chromosphere (for T>6300 K) and transition region yields reasonably good matches for all the observed lines. This value is marginally consistent with the most commonly accepted photospheric value: A(He)=0.085.Comment: 34 pages + 13 figures; to be published in Ap

Efficient Global Illumination for Morphable Models

We propose an efficient self-shadowing illumination model for Morphable Models. Simulating self-shadowing with ray casting is computationally expensive which makes them impractical in Analysis-by-Synthesis methods for object reconstruction from single images. Therefore, we propose to learn self-shadowing for Morphable Model parameters directly with a linear model. Radiance transfer functions are a powerful way to represent self-shadowing used within the precomputed radiance transfer framework (PRT). We build on PRT to render deforming objects with self-shadowing at interactive frame rates. It can be illuminated efficiently by environment maps represented with spherical harmonics. The result is an efficient global illumination method for Morphable Models, exploiting an approximated radiance transfer. We apply the method to fitting Morphable Model parameters to a single image of a face and demonstrate that considering self-shadowing improves shape reconstruction