Abstract Similar to computer graphics, the digital approach of holography (Computer Genarated Holograms) inherently samples the world. Calculating CGHs needs additional phase-related calculations, elevating computational demands.These calculations can make the development time excessively long or, in the worst case, unaffordable. Our approach, Partial Monte Carlo Sampling (PMCS), calculates CGHs via Monte Carlo techniques. By varying sampling resolution and ray percentages, reasonable quality is achieved, even with fewer rays. Quality analysis employing RMSE and CC reveals that reducing ray percentages does not severely compromise image quality. Both simulated and laboratory holograms display consistent trends, showcasing improved quality with increased rays and resolution. A direct relationship is established between image quality and computational time, addressing specific needs.

Abstract Computational simulations of flocks and crowds have typically been processed by a set of logic or syntactic rules. In recent decades, a new generation of systems has emerged from dynamicist approaches in which the agents and the environment are treated as a pair of dynamical systems coupled informationally and mechanically. Their spontaneous interactions allow them to achieve the desired behavior. The main proposition assumes that the agent does not need a full model or to make inferences before taking actions; rather, the information necessary for any action can be derived from the environment with simple computations and very little internal state. In this paper, we present a simulation framework in which the agents are endowed with a sensing device, an oscillator network as controller and actuators to interact with the environment. The perception device is designed as an optic array emulating the principles of the animal retina, which assimilates stimuli resembling optic flow to be captured from the environment. The controller modulates informational variables to action variables in a sensory‐motor flow. Our approach is based on the Kuramoto model that describes mathematically a network of coupled phase oscillators and the use of evolutionary algorithms, which is proved to be capable of synthesizing minimal synchronization strategies based on the dynamical coupling between agents and environment. We carry out a comparative analysis with classical implementations taking into account several criteria. It is concluded that we should consider replacing the metaphor of symbolic information processing by that of sensory‐motor coordination in problems of multi‐agent organizations. Copyright © 2015 John Wiley & Sons, Ltd.

Abstract In the domain of virtual agents modeling, computationalist approaches tend to predominate. The lack of plausibility of the rules in nature provides models with a low capacity to generalize and a very limited insight into behavioral phenomena. An alternative view is that behavior could emerge as a whole from the basic principles of non‐linear dynamics that underlie such behavior in the environment. This paper presents a dynamic agent endowed with a sensing device, a controller and actuators to interact with the environment. The control architecture is based on ordinary differential equations with the function of modulating the stimulus signals to action signals under a sensory‐motor flow. The parameter values are defined in an evolutionary process depending on the task to be performed. A series of experiments are presented to illustrate certain qualities of our model such as the adaptability to change, a highly intuitive and flexible design methodology, and a high degree of individual autonomy, among others. We think this kind of modeling is useful in the animation world for modeling flocks, crowds, and swarms as a valid alternative to other less parsimonious techniques.

Intermittency is ubiquitous in animal behavior. We depict a coordination problem that is part of the more general structure of intermittent adaptation: the adjustment-deployment dilemma. It captures the intricate compromise between the time spent in adjusting a response and the time used to deploy it: The adjustment process improves fitness with time, but during deployment fitness of the solution decays as environmental conditions change. We provide a formal characterization of the dilemma, and solve it using computational methods. We find that the optimal solution always results in a high intermittency between adjustment and deployment around a non-maximal fitness value. Furthermore we show that this non-maximal fitness value is directly determined by the ratio between the exponential coefficient of the fitness increase during adjustment and that of its decay coefficient during deployment. We compare the model results with experimental data obtained from observation and measurement of intermittent behavior in animals. Among other phenomena, the model is able to predict the uneven distribution of average duration of search and motion phases found among various species such as fishes, birds, and lizards. Despite the complexity of the problem, it can be shown to be solved by relatively simple mechanisms. We find that a model of a single continuous-time recurrent neuron, with the same parametric configuration, is capable of solving the dilemma for a wide set of conditions. We finally hypothesize that many of the different patterns of intermittent behavior found in nature might respond to optimal solutions of complexified versions of the adjustment-deployment dilemma under different constraints.

In this article, we derive a physically-based model for simulating rainbows. Previous techniques for simulating rainbows have used either geometric optics (ray tracing) or Lorenz-Mie theory. Lorenz-Mie theory is by far the most accurate technique as it takes into account optical effects such as dispersion, polarization, interference, and diffraction. These effects are critical for simulating rainbows accurately. However, as Lorenz-Mie theory is restricted to scattering by spherical particles, it cannot be applied to real raindrops which are nonspherical, especially for larger raindrops. We present the first comprehensive technique for simulating the interaction of a wavefront of light with a physically-based water drop shape. Our technique is based on ray tracing extended to account for dispersion, polarization, interference, and diffraction. Our model matches Lorenz-Mie theory for spherical particles, but it also enables the accurate simulation of nonspherical particles. It can simulate many different rainbow phenomena including double rainbows and supernumerary bows. We show how the nonspherical raindrops influence the shape of the rainbows, and we provide a simulation of the rare twinned rainbow, which is believed to be caused by nonspherical water drops.

Intermittent behaviour (movement interspersed with pauses) is a broad biological phenomenon which is observed in organisms ranging from protozoans to mammals. We depict a coordination problem that is part of the general structure of intermittent behaviour: the adjustment-deployment dilemma. This dilemma captures the difficult compromise between the time spent in adjusting a response and the time used to deploy it: the adjustment process improves fitness with time but we also assume that such fitness decays with time (e.g. environmental conditions change), if you spend very little time adjusting the fitness of the action is poor, but if you spent too much time before deployment the result is no longer valid. We provide a mathematical model of the dilemma, general enough to be applicable to different instances of it. An optimal solution is then simulated and analysed, the result shows that the optimal strategy is the one that maximizes the number of interactions with the environment. We explore the biological significance of such results and provide a minimal mechanism capable to instantiate an optimal solution. We conclude with a summary of the contributions of the present work and suggest potentially fruitful areas of future work.

Abstract This paper introduces a new method for simulating homogeneous subsurface light transport in translucent objects. Our approach is based on irradiance convolutions over a multi‐layered representation of the volume for light transport, which is general enough to obtain plausible depictions of translucent objects based on the diffusion approximation. We aim at providing an efficient physically based algorithm that can apply arbitrary diffusion profiles to general geometries. We obtain accurate results for a wide range of materials, on par with the hierarchical method by Jensen and Buhler.

Abstract 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.

Abstract Motion blur is a fundamental cue in the perception of objects in motion. This phenomenon manifests as a visible trail along the trajectory of the object and is the result of the combination of relative motion and light integration taking place in film and electronic cameras. In this work, we analyse the mechanisms that produce motion blur in recording devices and the methods that can simulate it in computer generated images. Light integration over time is one of the most expensive processes to simulate in high‐quality renders, as such, we make an in‐depth review of the existing algorithms and we categorize them in the context of a formal model that highlights their differences, strengths and limitations. We finalize this report proposing a number of alternative classifications that will help the reader identify the best technique for a particular scenario.

Motion blur is a frequent requirement for the rendering of high-quality animated images. However, the computational resources involved are usually higher than those for images that have not been temporally antialiased. In this article we study the influence of high-level properties such as object material and speed, shutter time, and antialiasing level. Based on scenes containing variations of these parameters, we design different psychophysical experiments to determine how influential they are in the perception of image quality. This work gives insights on the effects these parameters have and exposes certain situations where motion blurred stimuli may be indistinguishable from a gold standard. As an immediate practical application, images of similar quality can be produced while the computing requirements are reduced. Algorithmic efforts have traditionally been focused on finding new improved methods to alleviate sampling artifacts by steering computation to the most important dimensions of the rendering equation. Concurrently, rendering algorithms can take advantage of certain perceptual limits to simplify and optimize computations. To our knowledge, none of them has identified nor used these limits in the rendering of motion blur. This work can be considered a first step in that direction.

Abstract BqR‐Tree, the data structure presented in this paper is an improved R‐Tree data structure based on a quadtree spatial partitioning which improves the rendering speed of the usual R‐trees when view‐culling is implemented, especially in urban scenes. The city is split by means of a spatial quadtree partition and the block is adopted as the basic urban unit. One advantage of blocks is that they can be easily identified in any urban environment, regardless of the origins and structure of the input data. The aim of the structure is to accelerate the visualization of complex scenes containing not only static but dynamic elements. The usefulness of the structure has been tested with low structured data, which makes its application appropriate to almost all city data. The results of the tests show that when using the BqR‐Tree structure to perform walkthroughs and flights, rendering times vastly improve in comparison to the data structures which have yielded best results to date, with average improvements of around 30%.

Abstract Simulating the in‐water ocean light field is a daunting task. Ocean waters are one of the richest participating media, where light interacts not only with water molecules, but with suspended particles and organic matter as well. The concentration of each constituent greatly affects these interactions, resulting in very different hues. Inelastic scattering events such as fluorescence or Raman scattering imply energy transfers that are usually neglected in the simulations. Our contributions in this paper are a bio‐optical model of ocean waters suitable for computer graphics simulations, along with an improved method to obtain an accurate solution of the in‐water light field based on radiative transfer theory. The method provides a link between the inherent optical properties that define the medium and its apparent optical properties, which describe how it looks. The bio‐optical model of the ocean uses published data from oceanography studies. For inelastic scattering we compute all frequency changes at higher and lower energy values, based on the spectral quantum efficiency function of the medium. The results shown prove the usability of the system as a predictive rendering algorithm. Areas of application for this research span from underwater imagery to remote sensing; the resolution method is general enough to be usable in any type of participating medium simulation.

We present a powerful technique to simulate and approximate caustics in images. Our algorithm is designed to produce good results without the need to painstakingly paint over pixels. The ability to edit global illumination through image processing allows interaction with images at a level which has not yet been demonstrated, and significantly augments and extends current image-based material editing approaches. We show by means of a set of psychophysical experiments that the resulting imagery is visually plausible and on par with photon mapping, albeit without the need for hand-modeling the underlying geometry.

GIGA (the Advanced Computer Graphics Group from the University of Zaragoza) has developed two packages, code-named ALEPH and SICARA3D. Those systems are capable of both calculating light distribution in complex environments, based on a rigorous simulation of the physical phenomena involved, and visualizing the results in a photorealistic way, including models of the HVS (human visual system) implemented in a third package code-named S/spl middot/E/spl middot/K/spl middot/E/spl middot/R. Our systems support, as a remarkable difference with respect to all other known systems like RADIANCE ([G.J. Ward, (1994)]), a spectral management of lighting magnitudes, instead of working with simple RGB. We have also added to this framework the power of low-cost CAVE immersive systems. With this combination, we include stereoscopy and a collaborative environment to the reliability of the numerical results and the realistic aspect of the imagery.

In this paper, it is described a method of curved ray tracing capable of depicting phenomena that arise, under certain conditions, when light propagates through an inhomogeneous atmosphere. As an example application the distortions in the spherical shape of the sun during sunsets are modelled, including split suns, flattened suns and double suns. Nevertheless, the method is general and can be applied to any media in which the index of refraction is a function of the position

Abstract The aim of the work presented here is to generalize a system, developed to treat general participating media, to make it capable of considering volumetric inelastic processes such as fluorescence. Our system, based on the discrete ordinates method, is adequate to treat a complex participating medium such as natural waters as it is prepared to deal with not only anisotropic but also highly peaked phase functions, as well as to consider the spectral behaviour of the medium's characteristic parameters. It is also able to generate detailed quantitative illumination information, such as the amount of light that reaches the medium boundaries or the amount of light absorbed in each of the medium voxels. First, we present an extended form of the radiative transfer equation to incorporate inelastic volumetric phenomena. Then, we discuss the necessary changes in the general calculation scheme to include inelastic scattering. We have applied all this to consider the most common inelastic effect in natural waters: fluorescence in chlorophyll‐a. Copyright © 2004 John Wiley & Sons, Ltd.

We present a data structure specially geared toward the definition and management of synthetic actors in real-time computer graphics. The relation between our proposed data structure and the Silicon Graphics API Performer/spl reg/ makes its implementation possible on a low-cost real-time platform thanks to current accelerating cards. We demonstrate how our data structure is used to generate motion by means of two different applications. Both of them make use of direct and inverse kinematics and may use motion capture. ARTgraph is a development environment devoted to the creation of high-quality real-time 3D-graphics applications (basically, 3D games) and the ALVW system is a general platform that provides and coordinates a sensing-analysis-acting loop to provide behavior for synthetic actors in their own scenario. The aim of this paper is to contribute to the standardization process of multiplatform synthetic actor programs or libraries.

Abstract In this paper we study a finite element interpolation method for fitting discontinuous parametric surfaces when the data points are the nodes of a curvilinear grid. Quality control of the interpolating surfaces is also considered, focussing on the display of isophotes and reflection lines using ray tracing techniques. Finally, graphical and numerical examples are given.