10,249 research outputs found

    Pigmentation pattern formation in butterflies: experiments and models

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    Butterfly pigmentation patterns are one of the most spectacular and vivid examples of pattern formation in biology. They have attracted much attention from experimentalists and theoreticians, who have tried to understand the underlying genetic, chemical and physical processes that lead to patterning. In this paper, we present a brief review of this field by first considering the generation of the localised, eyespot, patterns and then the formation of more globally controlled patterns. We present some new results applied to pattern formation on the wing of the mimetic butterfly Papilio dardanus. To cite this article: H.F. Nijhout et al., C. R. Biologies 326 (2003)

    Computational Light Transport for Forward and Inverse Problems.

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    El transporte de luz computacional comprende todas las técnicas usadas para calcular el flujo de luz en una escena virtual. Su uso es ubicuo en distintas aplicaciones, desde entretenimiento y publicidad, hasta diseño de producto, ingeniería y arquitectura, incluyendo el generar datos validados para técnicas basadas en imagen por ordenador. Sin embargo, simular el transporte de luz de manera precisa es un proceso costoso. Como consecuencia, hay que establecer un balance entre la fidelidad de la simulación física y su coste computacional. Por ejemplo, es común asumir óptica geométrica o una velocidad de propagación de la luz infinita, o simplificar los modelos de reflectancia ignorando ciertos fenómenos. En esta tesis introducimos varias contribuciones a la simulación del transporte de luz, dirigidas tanto a mejorar la eficiencia del cálculo de la misma, como a expandir el rango de sus aplicaciones prácticas. Prestamos especial atención a remover la asunción de una velocidad de propagación infinita, generalizando el transporte de luz a su estado transitorio. Respecto a la mejora de eficiencia, presentamos un método para calcular el flujo de luz que incide directamente desde luminarias en un sistema de generación de imágenes por Monte Carlo, reduciendo significativamente la variancia de las imágenes resultantes usando el mismo tiempo de ejecución. Asimismo, introducimos una técnica basada en estimación de densidad en el estado transitorio, que permite reusar mejor las muestras temporales en un medio parcipativo. En el dominio de las aplicaciones, también introducimos dos nuevos usos del transporte de luz: Un modelo para simular un tipo especial de pigmentos gonicromáticos que exhiben apariencia perlescente, con el objetivo de proveer una forma de edición intuitiva para manufactura, y una técnica de imagen sin línea de visión directa usando información del tiempo de vuelo de la luz, construida sobre un modelo de propagación de la luz basado en ondas.<br /

    The Appearance of Platelet-Polymer Composite Coatings: Microstructural Characterization, Hybrid Modeling, and Predictive Design.

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    The appearance of a platelet-containing polymer composite coating is governed by the microstructure and optical properties included scattering particles and platelets. Many models attempt to predict the coating's appearance, but do not utilize the complete 3D-microstructure, reducing their predictive utility. In this thesis, laser scanning confocal microscopy was used to measure the effect of platelet orientation on angle-dependent lightness, and quantify the spacing between platelets, from which a new microstructural property, the gap factor, was determined. The gap factor is a measure of the average gap size between platelets per unit material surface length. It ranged from 0 to 2 for the systems studied in this thesis. An increase in gap factor of about 0.1, keeping the orientation similar, reduced the near-specular lightness of the physical samples by more than 20%. A 3D hybrid-simulation was created using wave-optics to simulate the bidirectional-reflection-distribution-function (BRDF) for individual platelets. This was combined with ray-tracing to quantify the scattering behavior of a platelet array. This model more accurately predicted the lightness of a silver paint sample than an orientation-based microfacet-model, and was used to study how the surface roughness of the platelets influences lightness. The lightness at 15 degrees off-specular was about 130 when the root-mean square of the amplitude of the roughness, sigma(RMS), was much less than the wavelength of light. Lightness reduced to about 80 when sigma(RMS) was about equal to the wavelength of light. This effect of sigma(RMS) on lightness was found to be more significant with decreases in the roughness correlation length. The hybrid model was also used to study how width, thickness, and volume concentration of the platelets change the near-specular and backscattered lightness. The observed reduction in near-specular lightness with gap factor was verified. However, the resultant 2nd-order exponential decay was weaker than observed. This was attributed wave-scattering by faces and edges, behavior not included in the current model, but may be added in the future. This hybrid model can be used in the future to design unique microstructures to produce new and novel visual or functional effects using manufacturing techniques such as 3D-printing.PhDMaterials Science and EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/133404/1/cseubert_1.pd

    The role of UV in crab spider signals: effects on perception by prey and predators

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    Australian crab spiders Thomisus spectabilis sit on the petals of flowers and ambush prey such as honeybees. White-coloured T. spectabilis reflect in the UV (UV+ spiders) and previous research has shown that their presence, curiously, attracts honeybees to daisies. We applied an UV-absorber (Parsol®) to create UV-absorbing (UV–) spiders that did not reflect any light below 395 nm wavelength. These physical changes of visual signals generated by crab spiders caused honeybees to avoid flowers with UV– spiders on their petals. They also affected the perception of UV– spiders by honeybees and a potential avian predator (blue tits). Compared to UV+ spiders, UV– spiders produced less excitation of the UV-photoreceptors in honeybees and blue tits, which translated into a reduced UV-receptor contrast and a reduced overall colour contrast between UV– spiders and daisy petals. Our results reveal that a clean physical elimination of reflection in the UV range affects perception in predators and prey and ultimately changes the behaviour of prey.7 page(s

    Editorial: biodegradable materials

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    This Special Issue “Biodegradable Materials” features research and review papers concerning recent advances on the development, synthesis, testing and characterisation of biomaterials. These biomaterials, derived from natural and renewable sources, offer a potential alternative to existing non-biodegradable materials with application to the food and biomedical industries amongst many others. In this Special Issue, the work is expanded to include the combined use of fillers that can enhance the properties of biomaterials prepared as films. The future application of these biomaterials could have an impact not only at the economic level, but also for the improvement of the environment

    Virtual Cleaning of Works of Art Using Deep Learning Based Approaches

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    Virtual cleaning of art is a key process that conservators apply to see the likely appearance of the work of art they have aimed to clean, before the process of cleaning. There have been many different approaches to virtually clean artworks but having to physically clean the artwork at a few specific places of specific colors, the need to have pure black and white paint on the painting and their low accuracy are only a few of their shortcomings prompting us to propose deep learning based approaches in this research. First we report the work we have done in this field focusing on the color estimation of the artwork virtual cleaning and then we describe our methods for the spectral reflectance estimation of artwork in virtual cleaning. In the color estimation part, a deep convolutional neural network (CNN) and a deep generative network (DGN) are suggested, which estimate the RGB image of the cleaned artwork from an RGB image of the uncleaned artwork. Applying the networks to the images of the well-known artworks (such as the Mona Lisa and The Virgin and Child with Saint Anne) and Macbeth ColorChecker and comparing the results to the only physics-based model (which is the first model that has approached the issue of virtual cleaning from the physics-point of view, hence our reference to compare our models with) shows that our methods outperform that model and have great potentials of being applied to the real situations in which there might not be much information available on the painting, and all we have is an RGB image of the uncleaned artwork. Nonetheless, the methods proposed in the first part, cannot provide us with the spectral reflectance information of the artwork, therefore, the second part of the dissertation is proposed. This part focuses on the spectral estimation of the artwork virtual cleaning. Two deep learning-based approaches are also proposed here; the first one is deep generative network. This method receives a cube of the hyperspectral image of the uncleaned artwork and tries to output another cube which is the virtually cleaned hyperspectral image of the artwork. The second approach is 1D Convolutional Autoencoder (1DCA), which is based on 1D convolutional neural network and tries to find the spectra of the virtually cleaned artwork using the spectra of the physically cleaned artworks and their corresponding uncleaned spectra. The approaches are applied to hyperspectral images of Macbeth ColorChecker (simulated in the forms of cleaned and uncleaned hyperspectral images) and the \u27Haymakers\u27 (real hyperspectral images of both cleaned and uncleaned states). The results, in terms of Euclidean distance and spectral angle between the virtually cleaned artwork and the physically cleaned one, show that the proposed approaches have outperformed the physics-based model, with DGN outperforming the 1DCA. Methods proposed herein do not rely on finding a specific type of paint and color on the painting first and take advantage of the high accuracy offered by deep learning-based approaches and they are also applicable to other paintings

    An Introduction to Light Interaction with Human Skin

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    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

    A viscous paint model for interactive applications

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    We present a viscous paint model for use in an interactive painting system based on the well-known Stokes’ equations for viscous flow. Our method is, to our knowledge, the first unconditionally stable numerical method that treats viscous fluid with a free surface boundary. We have also developed a real-time implementation of the Kubelka-Munk reflectance model for pigment mixing, compositing and rendering entirely on graphics hardware, using programmable fragment shading capabilities. We have integrated our paint model with a prototype painting system, which demonstrates the model’s effectiveness in rendering viscous paint and capturing a thick, impasto-like style of painting. Several users have tested our prototype system and were able to start creating original art work in an intuitive manner not possible with the existing techniques in commercial systems
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