On this mixture, a Continuous Projection operator is applied, which efficiently produces an L1 reconstruction of 72K point positions (c) at ∼ 9 FPS. In contrast, an L2 reconstruction (d) with small feature-preserving kernel exhibits heavily visible noise (top), while a larger kernel biases and oversmoothes the result (bottom). Our method runs at up to 7 times the speed of a fast GPU implementation of standard WLOP while providing comparable or even better quality, allowing for interactive robust reconstruction of unordered dynamic point sets. AbstractWith better and faster acquisition devices comes a demand for fast robust reconstruction algorithms, but no L1-based technique has been fast enough for online use so far. In this paper, we present a novel continuous formulation of the weighted locally optimal projection (WLOP) operator based on a Gaussian mixture describing the input point density. Our method is up to 7 times faster than an optimized GPU implementation of WLOP, and achieves interactive frame rates for moderately sized point clouds. We give a comprehensive quality analysis showing that our continuous operator achieves a generally higher reconstruction quality than its discrete counterpart. Additionally, we show how to apply our continuous formulation to spherical mixtures of normal directions, to also achieve a fast robust normal reconstruction.

Astrophysical jets emanating from different systems are one of the most spectacular and enigmatic phenomena pervading the Universe. These jets are typically bipolar and span hundreds of thousands of light years, some even longer than the diameter of our Milky Way. The study of the disc-jet systems is motivated by the observed correlation between ejection and accretion signatures and is still under debate. It was shown in our previous work the crucial role of thermal conduction in the dynamics of a thin viscous resistive accretion disc orbiting a central object and was provided an unprecedented wealth of discussion that has advanced our understanding of the inflow process. In this work, we expand our exploration by addressing the most outstanding basic questions concerning the launching, acceleration and collimation processes of the jet in presence of thermal conduction. We also tackle in depth-analysis the effects of this physical ingredient on the time evolution of temperature and on mass fluxes such as inflow and outflow rates. We performed a series of 2.5 D non-relativistic time-dependent numerical calculations of a disc-jet system using the PLUTO code. Our results revealed compelling evidence that thermal conduction contributes to launching a faster and more collimated jet. The mass extracted from the disc via the outflow channel is also affected by the presence of thermal conduction in the sense that the ejection efficiency is significantly improved.

With the rise of virtual reality experiences for applications in entertainment, industry, science and medicine, the evaluation of human motion in immersive environments is becoming more important. By analysing the motion of virtual reality users, design choices and training progress in the virtual environment can be understood and improved. Since the motion is captured in a virtual environment, performing the analysis in the same environment provides a valuable context and guidance for the analysis. We have created a visual analysis system that is designed for immersive visualisation and exploration of human motion data. By combining suitable data mining algorithms with immersive visualisation techniques, we facilitate the reasoning and understanding of the underlying motion. We apply and evaluate this novel approach on a relevant VR application domain to identify and interpret motion patterns in a meaningful way.

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