Affordable spectral measurements of translucent materials

We present a spectral measurement approach for the bulk optical properties of translucent materials using only low-cost components. We focus on the translucent inks used in full-color 3D printing, and develop a technique with a high spectral resolution, which is important for accurate color reproduction. We enable this by developing a new acquisition technique for the three unknown material parameters, namely, the absorption and scattering coefficients, and its phase function anisotropy factor, that only requires three point measurements with a spectrometer. In essence, our technique is based on us finding a three-dimensional appearance map, computed using Monte Carlo rendering, that allows the conversion between the three observables and the material parameters. Our measurement setup works without laboratory equipment or expensive optical components. We validate our results on a 3D printed color checker with various ink combinations. Our work paves a path for more accurate appearance modeling and fabrication even for low-budget environments or affordable embedding into other devices

Robust and practical measurement of volume transport parameters in solid photo-polymer materials for 3D printing

Volumetric light transport is a pervasive physical phenomenon, and therefore its accurate simulation is important for a broad array of disciplines. While suitable mathematical models for computing the transport are now available, obtaining the necessary material parameters needed to drive such simulations is a challenging task: direct measurements of these parameters from material samples are seldom possible. Building on the inverse scattering paradigm, we present a novel measurement approach which indirectly infers the transport parameters from extrinsic observations of multiple-scattered radiance. The novelty of the proposed approach lies in replacing structured illumination with a structured reflector bonded to the sample, and a robust fitting procedure that largely compensates for potential systematic errors in the calibration of the setup. We show the feasibility of our approach by validating simulations of complex 3D compositions of the measured materials against physical prints, using photo-polymer resins. As presented in this paper, our technique yields colorspace data suitable for accurate appearance reproduction in the area of 3D printing. Beyond that, and without fundamental changes to the basic measurement methodology, it could equally well be used to obtain spectral measurements that are useful for other application areas

An Optical Digital Twin for Underwater Photogrammetry: GEODT - A Geometrically Verified Optical Digital Twin for Development, Evaluation, Training, Testing and Tuning of Multi-Media Refractive Algorithms

Most parts of the Earth’s surface are situated in the deep ocean. To explore this visually rather adversarial environment with cameras, they have to be protected by pressure housings. These housings, in turn, need interfaces to the world, enduring extreme pressures within the water column. Commonly, a flat window or a half-sphere of glass, called flat-port or dome-port, respectively is used to implement such kind of interface. Hence, multi-media interfaces, between water, glass and air are introduced, entailing refraction effects in the images taken through them. To obtain unbiased 3D measurements and to yield a geometrically faithful reconstruction of the scene, it is mandatory to deal with the effects in a proper manner. Hence, we propose an optical digital twin of an underwater environment, which has been geometrically verified to resemble a real water lab tank that features the two most common optical interfaces. It can be used to develop, evaluate, train, test and tune refractive algorithms. Alongside this paper, we publish the model for further extension, jointly with code to dynamically generate samples from the dataset. Finally, we also publish a pre-rendered dataset ready for use at https://git.geomar.de/david-nakath/geodt

Modelado biofísico de la evolución de la apariencia de melanomas.

Los melanomas son un tipo de cáncer de piel propiciado por la división descontrolada de melanocitos, un tipo de células encargadas de la producción de la melanina. La melanina es un cromóforo que juega un papel fundamental en la apariencia de la piel. Además, durante su desarrollo el melanoma afecta notablemente a la vasculatura de la misma y por lo tanto a la concentración de hemoglobina, otro cromóforo clave para la apariencia de la piel. Sin embargo, pese a la prevalencia de los melanomas, su modelado preciso ha sido generalmente ignorado en informática gráfica, centrada fundamentalmente en modelar piel sana. Este TFM presenta un modelado biofísico de este tipo de afección, modelando la concentración de melanina y hemoglobina en función del estado de desarrollo del melanoma. Para ello se ha implementado un modelo biofísico de simulación de melanomas, que modela la evolución del mismo desde estadios tempranos, a partir del cual se han podido extraer las concentraciones de melanina y hemoglobina en distintas fases de su crecimiento. A partir de estas concentraciones, se ha podido obtener las propiedades ópticas de la piel alrededor de dicho melanoma, e introducir en un simulador de transporte de luz basado en física. Finalmente, hemos demostrado que dichas simulaciones son capaces de aproximar la apariencia de dichos melanomas en simulación, lo cual tiene múltiples aplicaciones especialmente en el entrenamiento de nuevas técnicas de diagnóstico basadas en aprendizaje automático. <br /

Generation of realistic skydome images

Generation of realistic skydome images We aim to generate realistic images of the sky with clouds using generative adversarial networks (GANs). We explore two GAN architectures, ProGAN and StyleGAN, and find that StyleGAN produces significantly better results. We also propose a novel architecture SuperGAN which aims to generate images at very high resolutions, which cannot be efficiently handled using state-of-art architectures. 1Generování realistických snímků obloh Naším cílem je generovat realistické obrázky oblohy s oblačností pomocí generativních kompetitivních sítí (GAN). Zkoumáme dvě architektury GANů, ProGAN a StyleGAN, a zjišťujeme, že StyleGAN dosahuje významně lepších výsledků. Pro generování obrázků ve velmi vysokém rozlišení, které nemůže být efektivně zpracováno soudobými architekturami GANů, navrhujeme novou architekturu SuperGAN. 1Department of Software and Computer Science EducationKatedra softwaru a výuky informatikyMatematicko-fyzikální fakultaFaculty of Mathematics and Physic