<![CDATA[ IEEE Transactions on Visualization and Computer Graphics - new TOC ]]>
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TOC Alert for Publication# 2945 2017November 23<![CDATA[Editor's Note]]>231224942495140<![CDATA[A Simple Push-Pull Algorithm for Blue-Noise Sampling]]>2312249625082507<![CDATA[A Statistical Direct Volume Rendering Framework for Visualization of Uncertain Data]]>2312250925201018<![CDATA[Creative Virtual Tree Modeling Through Hierarchical Topology-Preserving Blending]]>morph, grow and wilt are introduced and organized into a tree-structured blending scheduler, which not only introduces the randomness into the blending procedure but also wisely schedules the tasks to generate topology-aware blending sequences, contributing to a variety of resulting trees that exhibit diversities in both geometry and topology. Most significantly, multiple batches of blending can be executed in parallel, resulting in a rapid creation of a large repository of diverse trees.]]>2312252125341930<![CDATA[Data-Driven NPR Illustrations of Natural Flows in Chinese Painting]]>2312253525491966<![CDATA[Detecting When an Implicit Equation or a Rational Parametrization Defines a Conical or Cylindrical Surface, or a Surface of Revolution]]>surface defined by the equation, in the sense of Algebraic Geometry, is a cylindrical surface, a conical surface, or a surface of revolution. The algorithms are directly applicable to, and formulated in terms of, the implicit equation or the rational parametrization. When the surface is cylindrical, we show how to compute the direction of its rulings; when the surface is conical, we show how to compute its vertex; and when the surface is a surface of revolution, we show how to compute its axis of rotation directly from the defining equations.]]>231225502559279<![CDATA[Error-Bounded and Feature Preserving Surface Remeshing with Minimal Angle Improvement]]>$delta$, minimal interior angle $theta$ and maximum mesh complexity $N$ (number of vertices). The approximation error bound $delta$ is a hard constraint, while the other two criteria are modeled as optimization goals to guarantee feasibility. Our optimization framework applies carefully prioritized local operators in order to greedily search for the coarsest mesh with minimal interior angle above $theta$ and approximation error bounded by $delta$. Fast runtime is enabled by a local approximation error estimation, while impli-
it feature preservation is obtained by specifically designed vertex relocation operators. Experiments show that for reasonable angle bounds ( $theta leq 35^circ$) our approach delivers high-quality meshes with implicitly preserved features (no tagging required) and better balances between geometric fidelity, mesh complexity and element quality than the state-of-the-art.]]>2312256025731864<![CDATA[Pose-Inspired Shape Synthesis and Functional Hybrid]]>2312257425851461<![CDATA[Real-Time 3D Eye Performance Reconstruction for RGBD Cameras]]> $L0$-based optimization. Robustness and real-time optimization are achieved through the novel 3D Taylor expansion-based linearization. Furthermore, we propose an online bidirectional regression method to handle occlusions and other tracking failures on either of the two eyes from the information of the opposite eye. Experiments demonstrate that our technique achieves robust and accurate eye performance reconstruction for different iris appearances, with various head/face/eye motions, and under different lighting conditions.]]>2312258625981134<![CDATA[Scalable Visualization of Time-varying Multi-parameter Distributions Using Spatially Organized Histograms]]>2312259926121758<![CDATA[Surface Approximation via Asymptotic Optimal Geometric Partition]]>2312261326262482<![CDATA[Towards Zero-Waste Furniture Design]]>waste minimizing furniture design wherein based on the current design, the user is presented with design variations that result in less wastage of materials. Technically, we dynamically analyze material space layout to determine which parts to change and how , while maintaining original design intent specified in the form of design constraints. We evaluate the approach on various design scenarios, and demonstrate effective material usage that is difficult, if not impossible, to achieve without computational support.]]>2312262726401978<![CDATA[A Qualitative and Quantitative Evaluation of 8 Clear Sky Models]]>2312264126551481<![CDATA[Prescribed Velocity Gradients for Highly Viscous SPH Fluids with Vorticity Diffusion]]>231226562662797<![CDATA[2017 Reviewers List*]]>23122663266641