Based on a parallel scalable library for Coulomb interactions in particle systems, a comparison between the fast multipole method (FMM), multigrid-based methods, fast Fourier transform (FFT)-based methods, and a Maxwell solver is provided for the case of three-dimensional periodic boundary conditions. These methods are directly compared with respect to complexity, scalability, performance, and accuracy. To ensure comparable conditions for all methods and to cover typical applications, we tested all methods on the same set of computers using identical benchmark systems. Our findings suggest that, depending on system size and desired accuracy, the FMM- and FFT-based methods are most efficient in performance and stability.

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Object Object(a) (b) (c) Fig. 1. (a) The challenge of looking around the corner deals with the recovery of information about objects beyond the direct line of sight. In this illustration of a setting proposed by Velten et al. [2012], an unknown object is located in front of a wall, but additional obstacles occlude the object from any optical devices like light sources or cameras. Our only source of information are therefore indirect reflections off other surfaces (here, a planar "wall"). A point on the wall that is illuminated by an ultrashort laser pulse turns into an omnidirectional source of indirect light ("laser spot"). After scattering off the unknown object, some of that light arrives back at the wall, where it forms an optical "echo" or space-time response (shown are 2D slices) that can be picked up by a suitable camera. Locations on the wall can be interpreted as omnidirectional detector pixels that receive different mixtures of backscattered light contributions at different times. We assume that neither camera nor laser can directly illuminate or observe the object, leaving us with the indirect optical space-time response as the only source of information. Note that for the sake of clarity, laser source, camera, and occluder are not shown here. The complete setup is illustrated in Figure 2. (b) We propose a novel transient renderer to simulate such indirectly scattered light transport efficiently enough for use as a forward model in inverse problems. In this artistic visualization, light contributions removed by the shadow test are marked in red, and the net intensity in blue. Together with an optimization algorithm, the renderer can be used to reconstruct the geometry of objects outside the line of sight. (c) Left to right: ground-truth object geometry; reconstruction using a state-of-the-art method (ellipsoidal backprojection); reconstruction using the technique presented in this paper. Top row: BunnyGI dataset; bottom row: Mannequin1Laser dataset. Our method relies on highly efficient and near-physical forward simulation, and it exemplifies the use of computer graphics as a technical tool to solve inverse problems in other fields.Being able to see beyond the direct line of sight is an intriguing prospective and could benefit a wide variety of important applications. Recent work has demonstrated that time-resolved measurements of indirect diffuse light contain valuable information for reconstructing shape and reflectance properties of objects located around a corner. In this paper, we introduce a novel reconstruction scheme that, by design, produces solutions that are consistent with state-of-the-art physically-based rendering. Our method combines an efficient forward model (a custom renderer for time-resolved three-bounce indirect light transport) with an optimization framework to reconstruct object geometry in an analysis-by-synthesis sense. We evaluate our algorithm on a variety of synthetic and experimental input data, and show that it gracefully handles uncooperative scenes with high levels of no...

Soap bubbles are widely appreciated for their fragile nature and their colorful appearance. The natural sciences and, in extension, computer graphics, have comprehensively studied the mechanical behavior of films and foams, as well as the optical properties of thin liquid layers. In this paper, we focus on the dynamics of material flow within the soap film, which results in fascinating, extremely detailed patterns. This flow is characterized by a complex coupling between surfactant concentration and Marangoni surface tension. We propose a novel chemomechanical simulation framework rooted in lubrication theory, which makes use of a custom semi-Lagrangian advection solver to enable the simulation of soap film dynamics on spherical bubbles both in free flow as well as under body forces such as gravity or external air flow. By comparing our simulated outcomes to videos of real-world soap bubbles recorded in a studio environment, we show that our framework, for the first time, closely recreates a wide range of dynamic effects that are also observed in experiment.

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Light fields are a powerful concept in computational imaging and a mainstay in image-based rendering; however, so far their acquisition required either carefully designed and calibrated optical systems (micro-lens arrays), or multi-camera/multi-shot settings. Here, we show that fully calibrated light field data can be obtained from a single ordinary photograph taken through a partially wetted window. Each drop of water produces a distorted view on the scene, and the challenge of recovering the unknown mapping from pixel coordinates to refracted rays in space is a severely underconstrained problem. The key idea behind our solution is to combine ray tracing and low-level image analysis techniques (extraction of 2D drop contours and locations of scene features seen through drops) with state-of-the-art drop shape simulation and an iterative refinement scheme to enforce photo-consistency across features that are seen in multiple views. This novel approach not only recovers a dense pixel-to-ray mapping, but also the refractive geometry through which the scene is observed, to high accuracy. We therefore anticipate that our inherently self-calibrating scheme might also find applications in other fields, for instance in materials science where the wetting properties of liquids on surfaces are investigated.

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The recent years have given rise to a large number of techniques for “looking around corners”, i.e., for reconstructing or tracking occluded objects from indirect light reflections off a wall. While the direct view of cameras is routinely calibrated in computer vision applications, the calibration of non-line-of-sight setups has so far relied on manual measurement of the most important dimensions (device positions, wall position and orientation, etc.). In this paper, we propose a method for calibrating time-of-flight-based non-line-of-sight imaging systems that relies on mirrors as known targets. A roughly determined initialization is refined in order to optimize for spatio-temporal consistency. Our system is general enough to be applicable to a variety of sensing scenarios ranging from single sources/detectors via scanning arrangements to large-scale arrays. It is robust towards bad initialization and the achieved accuracy is proportional to the depth resolution of the camera system.