Sky Based Light Metering for High Dynamic Range Images

Image calibration requires both linearization of pixel values and scaling so that values in the image correspond to real‐world luminances. In this paper we focus on the latter and rather than rely on camera characterization, we calibrate images by analysing their content and metadata, obviating the need for expensive measuring devices or modeling of lens and camera combinations. Our analysis correlates sky pixel values to luminances that would be expected based on geographical metadata. Combined with high dynamic range (HDR) imaging, which gives us linear pixel data, our algorithm allows us to find absolute luminance values for each pixel—effectively turning digital cameras into absolute light meters. To validate our algorithm we have collected and annotated a calibrated set of HDR images and compared our estimation with several other approaches, showing that our approach is able to more accurately recover absolute luminance. We discuss various applications and demonstrate the utility of our method in the context of calibrated color appearance reproduction and lighting design.     

Continuous Self‐Collision Detection for Deformable Surfaces Interacting with Solid Models

In this paper, we propose a new continuous self‐collision detection (CSCD) method for a deformable surface that interacts with a simple solid model. The method is developed based on the radial‐view‐based culling method. Our method is suitable for the deformable surface that has large contact region with the solid model. The deformable surface may consist of small round‐shaped holes. At the pre‐processing stage, the holes of the deformable surface are filled with ghost triangles so as to make the mesh of the deformable surface watertight. An observer primitive (i.e. a point or a line segment) is computed so that it lies inside the solid model. At the runtime stage, the orientations of triangles with respect to the observer primitive are evaluated. The collision status of the deformable surface is then determined. We evaluated our method for several animations including virtual garments. Experimental results show that our method improves the process of CSCD.     

Spatio‐temporal geometry fusion for multiple hybrid cameras using moving least squares surfaces

Multi‐view reconstruction aims at computing the geometry of a scene observed by a set of cameras. Accurate 3D reconstruction of dynamic scenes is a key component for a large variety of applications, ranging from special effects to telepresence and medical imaging. In this paper we propose a method based on Moving Least Squares surfaces which robustly and efficiently reconstructs dynamic scenes captured by a calibrated set of hybrid color+depth cameras. Our reconstruction provides spatio‐temporal consistency and seamlessly fuses color and geometric information. We illustrate our approach on a variety of real sequences and demonstrate that it favorably compares to state‐of‐the‐art methods.     

Coded exposure HDR light‐field video recording

Capturing exposure sequences to compute high dynamic range (HDR) images causes motion blur in cases of camera movement. This also applies to light‐field cameras: frames rendered from multiple blurred HDR light‐field perspectives are also blurred. While the recording times of exposure sequences cannot be reduced for a single‐sensor camera, we demonstrate how this can be achieved for a camera array. Thus, we decrease capturing time and reduce motion blur for HDR light‐field video recording. Applying a spatio‐temporal exposure pattern while capturing frames with a camera array reduces the overall recording time and enables the estimation of camera movement within one light‐field video frame. By estimating depth maps and local point spread functions (PSFs) from multiple perspectives with the same exposure, regional motion deblurring can be supported. Missing exposures at various perspectives are then interpolated.     

Group‐in‐a‐Box Meta‐Layouts for Topological Clusters and Attribute‐Based Groups: Space‐Efficient Visualizations of Network Communities and Their Ties

An important part of network analysis is understanding community structures like topological clusters and attribute‐based groups. Standard approaches for showing communities using colour, shape, rectangular bounding boxes, convex hulls or force‐directed layout algorithms remain valuable, however our Group‐in‐a‐Box meta‐layouts add a fresh strategy for presenting community membership, internal structure and inter‐cluster relationships. This paper extends the basic Group‐in‐a‐Box meta‐layout, which uses a Treemap substrate of rectangular regions whose size is proportional to community size. When there are numerous inter‐community relationships, the proposed extensions help users view them more clearly: (1) the Croissant–Doughnut meta‐layout applies empirically determined rules for box arrangement to improve space utilization while still showing inter‐community relationships, and (2) the Force‐Directed layout arranges community boxes based on their aggregate ties at the cost of additional space. Our free and open source reference implementation in NodeXL includes heuristics to choose what we have found to be the preferable Group‐in‐a‐Box meta‐layout to show networks with varying numbers or sizes of communities. Case study examples, a pilot comparative user preference study (nine participants), and a readability measure‐based evaluation of 309 Twitter networks demonstrate the utility of the proposed meta‐layouts.     

Continuous Levels‐of‐Detail and Visual Abstraction for Seamless Molecular Visualization

Molecular visualization is often challenged with rendering of large molecular structures in real time. We introduce a novel approach that enables us to show even large protein complexes. Our method is based on the level‐of‐detail concept, where we exploit three different abstractions combined in one visualization. Firstly, molecular surface abstraction exploits three different surfaces, solvent‐excluded surface (SES), Gaussian kernels and van der Waals spheres, combined as one surface by linear interpolation. Secondly, we introduce three shading abstraction levels and a method for creating seamless transitions between these representations. The SES representation with full shading and added contours stands in focus while on the other side a sphere representation of a cluster of atoms with constant shading and without contours provide the context. Thirdly, we propose a hierarchical abstraction based on a set of clusters formed on molecular atoms. All three abstraction models are driven by one importance function classifying the scene into the near‐, mid‐ and far‐field. Moreover, we introduce a methodology to render the entire molecule directly using the A‐buffer technique, which further improves the performance. The rendering performance is evaluated on series of molecules of varying atom counts.     

Robust Treatment of Degenerate Elements in Interactive Corotational FEM Simulations

We address the problem of robust and efficient treatment of element collapse and inversion in corotational FEM simulations of deformable objects in two and three dimensions, and show that existing degeneration treatment methods have previously unreported flaws that seriously threaten robustness and physical plausibility in interactive applications. We propose a new method that avoids such flaws, yields faster and smoother degeneration recovery and extends the range of well‐behaved degenerate configurations without adding significant complexity or computational cost to standard explicit and quasi‐implicit solvers.     

4D MRI Flow Coupled to Physics‐Based Fluid Simulation for Blood‐Flow Visualization

Modern MRI measurements deliver volumetric and time‐varying blood‐flow data of unprecedented quality. Visual analysis of these data potentially leads to a better diagnosis and risk assessment of various cardiovascular diseases. Recent advances have improved the speed and quality of the imaging data considerably. Nevertheless, the data remains compromised by noise and a lack of spatiotemporal resolution. Besides imaging data, also numerical simulations are employed. These are based on mathematical models of specific features of physical reality. However, these models require realistic parameters and boundary conditions based on measurements. We propose to use data assimilation to bring measured data and physically‐based simulation together, and to harness the mutual benefits. The accuracy and noise robustness of the coupled approach is validated using an analytic flow field. Furthermore, we present a comparative visualization that conveys the differences between using conventional interpolation and our coupled approach.     

Scalable Realistic Rendering with Many‐Light Methods

Recent years have seen increasing attention and significant progress in many‐light rendering, a class of methods for efficient computation of global illumination. The many‐light formulation offers a unified mathematical framework for the problem reducing the full lighting transport simulation to the calculation of the direct illumination from many virtual light sources. These methods are unrivaled in their scalability: they are able to produce plausible images in a fraction of a second but also converge to the full solution over time. In this state‐of‐the‐art report, we give an easy‐to‐follow, introductory tutorial of the many‐light theory; provide a comprehensive, unified survey of the topic with a comparison of the main algorithms; discuss limitations regarding materials and light transport phenomena and present a vision to motivate and guide future research. We will cover both the fundamental concepts as well as improvements, extensions and applications of many‐light rendering.