Search results for "Computer Science - Graphics"

showing 5 items of 5 documents

Approximation of functions over manifolds : A Moving Least-Squares approach

2021

We present an algorithm for approximating a function defined over a $d$-dimensional manifold utilizing only noisy function values at locations sampled from the manifold with noise. To produce the approximation we do not require any knowledge regarding the manifold other than its dimension $d$. We use the Manifold Moving Least-Squares approach of (Sober and Levin 2016) to reconstruct the atlas of charts and the approximation is built on-top of those charts. The resulting approximant is shown to be a function defined over a neighborhood of a manifold, approximating the originally sampled manifold. In other words, given a new point, located near the manifold, the approximation can be evaluated…

Computational Geometry (cs.CG)FOS: Computer and information sciencesComputer Science - Machine LearningClosed manifolddimension reductionMachine Learning (stat.ML)010103 numerical & computational mathematicsComplex dimensionTopology01 natural sciencesMachine Learning (cs.LG)Volume formComputer Science - GraphicsStatistics - Machine Learningmanifold learningApplied mathematics0101 mathematicsfunktiotMathematicsManifold alignmentAtlas (topology)Applied Mathematicshigh dimensional approximationManifoldGraphics (cs.GR)Statistical manifold010101 applied mathematicsregression over manifoldsComputational Mathematicsout-of-sample extensionComputer Science - Computational Geometrynumeerinen analyysimonistotapproksimointimoving least-squaresCenter manifold
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Perceptually Optimized Image Rendering

2017

We develop a framework for rendering photographic images by directly optimizing their perceptual similarity to the original visual scene. Specifically, over the set of all images that can be rendered on a given display, we minimize the normalized Laplacian pyramid distance (NLPD), a measure of perceptual dissimilarity that is derived from a simple model of the early stages of the human visual system. When rendering images acquired with a higher dynamic range than that of the display, we find that the optimization boosts the contrast of low-contrast features without introducing significant artifacts, yielding results of comparable visual quality to current state-of-the-art methods, but witho…

FOS: Computer and information sciencesComputer Science - Artificial IntelligenceImage qualityComputer scienceComputer Vision and Pattern Recognition (cs.CV)Computer Science - Computer Vision and Pattern RecognitionComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONImage processing02 engineering and technologyLuminanceRendering (computer graphics)Computer Science - GraphicsOptics0202 electrical engineering electronic engineering information engineeringComputer visionPower functionComputingMethodologies_COMPUTERGRAPHICSbusiness.industryDynamic range020207 software engineeringAtomic and Molecular Physics and OpticsGraphics (cs.GR)Electronic Optical and Magnetic MaterialsArtificial Intelligence (cs.AI)Human visual system model020201 artificial intelligence & image processingComputer Vision and Pattern RecognitionArtificial intelligencebusinessImage compression
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A Robust Blind 3-D Mesh Watermarking Technique Based on SCS Quantization and Mesh Saliency for Copyright Protection

2019

Due to the recent demand of 3-D meshes in a wide range of applications such as video games, medical imaging, film special effect making, computer-aided design (CAD), among others, the necessity of implementing 3-D mesh watermarking schemes aiming to protect copyright has increased in the last decade. Nowadays, the majority of robust 3-D watermarking approaches have mainly focused on the robustness against attacks while the imperceptibility of these techniques is still a serious challenge. In this context, a blind robust 3-D mesh watermarking method based on mesh saliency and scalar Costa scheme (SCS) for Copyright protection is proposed. The watermark is embedded by quantifying the vertex n…

FOS: Computer and information sciencesComputer Science - Cryptography and SecurityComputer science[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingQuantization (signal processing)Data_MISCELLANEOUS020207 software engineeringWatermark02 engineering and technologyGraphics (cs.GR)Computer Science - Graphics[INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingComputer engineering0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingPolygon meshVertex normalQuantization (image processing)Digital watermarkingCryptography and Security (cs.CR)ComputingMilieux_MISCELLANEOUSSmoothing
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RTIndeX: Exploiting Hardware-Accelerated GPU Raytracing for Database Indexing

2023

Data management on GPUs has become increasingly relevant due to a tremendous rise in processing power and available GPU memory. Just like in the CPU world, there is a need for performant GPU-resident index structures to speed up query processing. Unfortunately, mapping indexes efficiently to the highly parallel and hard-to-program hardware is challenging and often fails to yield the desired performance and flexibility. Therefore, we advocate to take a different route. Instead of proposing yet another hand-tailored index, we investigate whether we can exploit an indexing mechanism that is already built into modern GPUs: The raytracing hardware accelerator provided by NVIDIA RTX cards. To do …

FOS: Computer and information sciencesComputer Science - GraphicsComputer Science - DatabasesDatabases (cs.DB)Graphics (cs.GR)
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Multi-GPU Accelerated Multi-Spin Monte Carlo Simulations of the 2D Ising Model

2010

A Modern Graphics Processing unit (GPU) is able to perform massively parallel scientific computations at low cost. We extend our implementation of the checkerboard algorithm for the two-dimensional Ising model [T. Preis et al., Journal of Chemical Physics 228 (2009) 4468–4477] in order to overcome the memory limitations of a single GPU which enables us to simulate significantly larger systems. Using multi-spin coding techniques, we are able to accelerate simulations on a single GPU by factors up to 35 compared to an optimized single Central Processor Unit (CPU) core implementation which employs multi-spin coding. By combining the Compute Unified Device Architecture (CUDA) with the Message P…

FOS: Computer and information sciencesComputer scienceMonte Carlo methodGraphics processing unitFOS: Physical sciencesGeneral Physics and AstronomyMathematical Physics (math-ph)Parallel computingGPU clusterComputational Physics (physics.comp-ph)Graphics (cs.GR)Computational scienceCUDAComputer Science - GraphicsHardware and ArchitectureIsing modelCentral processing unitGeneral-purpose computing on graphics processing unitsMassively parallelPhysics - Computational PhysicsMathematical Physics
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