Adaptive isocurves based rendering for freeform surfaces

Journal ArticleFreeform surface rendering is traditionally performed by approximating the surface with polygons and then rendering the polygons. This approach is extremely common because of the complexity in accurately rendering the surfaces directly. Recently, several papers presented methods to render surfaces as sequences of isocurves. Unfortunately, these methods start by assuming that an appropriate collection of isocurves has already been derived. The algorithms themselves neither automatically create an optimal or almost optimal set of isocurves so t h e whole surface would be correctly rendered without having pixels redundantly visited nor automatically compute the parameter spacing required between isocurves to guarantee such coverage. In this paper, a new algorithm is developed to fill these needs. An algorithm is introduced that automatically computes a set of almost optimal isocurves covering the entire surface area. This algorithm can be combined with a fast curve rendering method, to make surface rendering without polygonal approximation practical

WavePacket: A Matlab package for numerical quantum dynamics. III: Quantum-classical simulations and surface hopping trajectories

WavePacket is an open-source program package for numerical simulations in quantum dynamics. Building on the previous Part I [Comp. Phys. Comm. 213, 223-234 (2017)] and Part II [Comp. Phys. Comm. 228, 229-244 (2018)] which dealt with quantum dynamics of closed and open systems, respectively, the present Part III adds fully classical and mixed quantum-classical propagations to WavePacket. In those simulations classical phase-space densities are sampled by trajectories which follow (diabatic or adiabatic) potential energy surfaces. In the vicinity of (genuine or avoided) intersections of those surfaces trajectories may switch between surfaces. To model these transitions, two classes of stochastic algorithms have been implemented: (1) J. C. Tully's fewest switches surface hopping and (2) Landau-Zener based single switch surface hopping. The latter one offers the advantage of being based on adiabatic energy gaps only, thus not requiring non-adiabatic coupling information any more. The present work describes the MATLAB version of WavePacket 6.0.2 which is essentially an object-oriented rewrite of previous versions, allowing to perform fully classical, quantum-classical and quantum-mechanical simulations on an equal footing, i.e., for the same physical system described by the same WavePacket input. The software package is hosted and further developed at the Sourceforge platform, where also extensive Wiki-documentation as well as numerous worked-out demonstration examples with animated graphics are available

Font Rasterization, the State of Art

Modern personal computers and workstations enable text, graphics and images to be visualized in a resolution independent manner. Office documents can be visualized and printed in the same way on displays, page-printers and photocomposers. Personal computers like the PC and the MacIntosh incorporate advanced rasterization algorithms for the rendering of outline characters and graphics. In the nineties, advanced workstations will provide facilities for the generation of finely tuned gray-scale characters. This tutorial provides a survey of the basic algorithms for representing and rendering outline characters. Fast scan-conversion and filling algorithms as well as basic and advanced character outline grid-fitting techniques are presented. The philosophy and functionality of Adobe's Type 1 and Apple's TrueType typographic rendering systems are discussed

Ubiquitous Scalable Graphics: An End-to-End Framework using Wavelets

Advances in ubiquitous displays and wireless communications have fueled the emergence of exciting mobile graphics applications including 3D virtual product catalogs, 3D maps, security monitoring systems and mobile games. Current trends that use cameras to capture geometry, material reflectance and other graphics elements means that very high resolution inputs is accessible to render extremely photorealistic scenes. However, captured graphics content can be many gigabytes in size, and must be simplified before they can be used on small mobile devices, which have limited resources, such as memory, screen size and battery energy. Scaling and converting graphics content to a suitable rendering format involves running several software tools, and selecting the best resolution for target mobile device is often done by trial and error, which all takes time. Wireless errors can also affect transmitted content and aggressive compression is needed for low-bandwidth wireless networks. Most rendering algorithms are currently optimized for visual realism and speed, but are not resource or energy efficient on mobile device. This dissertation focuses on the improvement of rendering performance by reducing the impacts of these problems with UbiWave, an end-to-end Framework to enable real time mobile access to high resolution graphics using wavelets. The framework tackles the issues including simplification, transmission, and resource efficient rendering of graphics content on mobile device based on wavelets by utilizing 1) a Perceptual Error Metric (PoI) for automatically computing the best resolution of graphics content for a given mobile display to eliminate guesswork and save resources, 2) Unequal Error Protection (UEP) to improve the resilience to wireless errors, 3) an Energy-efficient Adaptive Real-time Rendering (EARR) heuristic to balance energy consumption, rendering speed and image quality and 4) an Energy-efficient Streaming Technique. The results facilitate a new class of mobile graphics application which can gracefully adapt the lowest acceptable rendering resolution to the wireless network conditions and the availability of resources and battery energy on mobile device adaptively

Resource optimization and dynamic state management in a collaborative virtual environment.

Yim-Pan Chui.Thesis (M.Phil.)--Chinese University of Hong Kong, 2001.Includes bibliographical references (leaves 126-132).Abstracts in English and Chinese.Abstract --- p.iiAcknowledgments --- p.vChapter 1 --- Introduction --- p.1Chapter 1.1 --- Introduction to Collaborative Virtual Environments --- p.1Chapter 1.2 --- Barriers to Resource Management and Optimization --- p.3Chapter 1.3 --- Thesis Contributions --- p.5Chapter 1.4 --- Application of this Research Work --- p.6Chapter 1.5 --- Thesis Organization --- p.6Chapter 2 --- Resource Optimization - Intelligent Server Partitioning --- p.9Chapter 2.1 --- Introduction --- p.9Chapter 2.2 --- Server Partitioning --- p.13Chapter 2.2.1 --- Related Works --- p.15Chapter 2.2.2 --- Global Optimization Approaches --- p.17Chapter 2.3 --- Hybrid Genetic Algorithm Paradigm --- p.17Chapter 2.3.1 --- Drawbacks of traditional GA --- p.18Chapter 2.3.2 --- Problem Modeling --- p.19Chapter 2.3.3 --- Discussion --- p.24Chapter 2.4 --- Results --- p.25Chapter 2.5 --- Concluding Remarks --- p.28Chapter 3 --- Dynamic State Management - Dead Reckoning of Attitude --- p.32Chapter 3.1 --- Introduction to Dynamic State Management --- p.32Chapter 3.2 --- The Dead Reckoning Approach --- p.35Chapter 3.3 --- Attitude Dead Reckoning by Quaternion --- p.37Chapter 3.3.1 --- Modeling of the Paradigm --- p.38Chapter 3.3.2 --- Prediction Step --- p.39Chapter 3.3.3 --- Convergence Step --- p.40Chapter 3.3.4 --- Overall Algorithm --- p.46Chapter 3.4 --- Results --- p.47Chapter 3.5 --- Conclusion --- p.51Chapter 4 --- Polynomial Attitude Extrapolation --- p.52Chapter 4.1 --- Introduction --- p.52Chapter 4.2 --- Related Works on Kalman Filtering --- p.53Chapter 4.3 --- Historical Propagation of Quaternion --- p.54Chapter 4.3.1 --- Cumulative Extrapolation --- p.54Chapter 4.3.2 --- Method I. Vandemonde Approach --- p.55Chapter 4.3.3 --- Method II. Lagrangian Approach --- p.58Chapter 4.4 --- History-Based Attitude Management --- p.60Chapter 4.4.1 --- Multi-order Prediction --- p.60Chapter 4.4.2 --- Adaptive Attitude Convergence --- p.63Chapter 4.4.3 --- Overall Algorithm --- p.67Chapter 4.5 --- Results --- p.69Chapter 4.6 --- Conclusion --- p.77Chapter 5 --- Forward Difference Approach on State Estimation --- p.78Chapter 5.1 --- Introduction --- p.78Chapter 5.2 --- Positional Forward Differencing --- p.79Chapter 5.3 --- Forward Difference on Quaternion Space --- p.80Chapter 5.3.1 --- Attitude Forward Differencing --- p.83Chapter 5.3.2 --- Trajectory Blending --- p.84Chapter 5.4 --- State Estimation --- p.86Chapter 5.5 --- Computational Efficiency --- p.87Chapter 5.6 --- Results --- p.88Chapter 5.7 --- Conclusion --- p.96Chapter 6 --- Predictive Multibody Kinematics --- p.98Chapter 6.1 --- Introduction --- p.98Chapter 6.2 --- Dynamic Management of Multibody System --- p.100Chapter 6.2.1 --- Multibody Representation --- p.100Chapter 6.2.2 --- Paradigm Overview --- p.101Chapter 6.3 --- Motion Estimation by Joint Extrapolation --- p.102Chapter 6.3.1 --- Individual Joint Extrapolation --- p.102Chapter 6.3.2 --- Forward Propagation of Joint State --- p.104Chapter 6.3.3 --- Pose Correction --- p.107Chapter 6.4 --- Limitations on Predictive Articulated State Management --- p.108Chapter 6.5 --- Implementation and Results --- p.109Chapter 6.6 --- Conclusion --- p.112Chapter 7 --- Complete System Architecture --- p.113Chapter 7.1 --- Server Cluster Model --- p.113Chapter 7.1.1 --- Peer-Server Systems --- p.114Chapter 7.1.2 --- Server Hierarchies --- p.114Chapter 7.2 --- Multi-Level Resource Management --- p.115Chapter 7.3 --- Aggregation of State Updates --- p.116Chapter 7.4 --- Implementation Issues --- p.117Chapter 7.4.1 --- Medical Visualization --- p.117Chapter 7.4.2 --- Virtual Walkthrough Application --- p.118Chapter 7.5 --- Conclusion --- p.119Chapter 8 --- Conclusions and Future directions --- p.121Chapter 8.1 --- Conclusion --- p.121Chapter 8.2 --- Future Research Directions --- p.122Chapter A --- Quaternion Basis --- p.124Chapter A.1 --- Basic Quaternion Mathematics --- p.124Chapter A.2 --- The Exponential and Logarithmic Maps --- p.125Bibliography --- p.12

The modelling of natural imperfections and an improved space filling curve halftoning technique.

by Tien-tsin Wong.Thesis (M.Phil.)--Chinese University of Hong Kong, 1994.Includes bibliographical references (leaves 72-79).Chapter 1 --- Introduction --- p.1Chapter 1.1 --- The Modelling of Natural Imperfections --- p.1Chapter 1.2 --- Improved Clustered-dot Space Filling Curve Halftoning Technique --- p.2Chapter 1.3 --- Structure of the Thesis --- p.3Chapter 2 --- The Modelling of Natural Imperfections --- p.4Chapter 2.1 --- Introduction --- p.4Chapter 2.2 --- Related Work --- p.6Chapter 2.2.1 --- Texture Mapping --- p.6Chapter 2.2.2 --- Blinn's Dusty Surfaces --- p.7Chapter 2.2.3 --- Imperfection Rule-based Systems --- p.7Chapter 2.3 --- Natural Surface Imperfections --- p.8Chapter 2.3.1 --- Dust Accumulation --- p.8Chapter 2.3.2 --- Scratching --- p.10Chapter 2.3.3 --- Rusting --- p.10Chapter 2.3.4 --- Mould --- p.11Chapter 2.4 --- New Modelling Framework for Natural Imperfections --- p.13Chapter 2.4.1 --- Calculation of Tendency --- p.13Chapter 2.4.2 --- Generation of Chaotic Pattern --- p.19Chapter 2.5 --- Modelling of Dust Accumulation --- p.21Chapter 2.5.1 --- Predicted Tendency of Dust Accumulation --- p.22Chapter 2.5.2 --- External Factors --- p.24Chapter 2.5.3 --- Generation of Fuzzy Dust Layer --- p.30Chapter 2.5.4 --- Implementation Issues --- p.31Chapter 2.6 --- Modelling of Scratching --- p.31Chapter 2.6.1 --- External Factor --- p.32Chapter 2.6.2 --- Generation of Chaotic Scratch Patterns --- p.35Chapter 2.6.3 --- Implementation Issues --- p.36Chapter 3 --- An Improved Space Filling Curve Halftoning Technique --- p.39Chapter 3.1 --- Introduction --- p.39Chapter 3.2 --- Review on Some Halftoning Techniques --- p.41Chapter 3.2.1 --- Ordered Dither --- p.41Chapter 3.2.2 --- Error Diffusion and Dither with Blue Noise --- p.42Chapter 3.2.3 --- Dot Diffusion --- p.43Chapter 3.2.4 --- Halftoning Along Space Filling Traversal --- p.43Chapter 3.2.5 --- Space Diffusion --- p.46Chapter 3.3 --- Improvements on the Clustered-Dot Space Filling Halftoning Method --- p.47Chapter 3.3.1 --- Selective Precipitation --- p.47Chapter 3.3.2 --- Adaptive Clustering --- p.50Chapter 3.4 --- Comparison With Other Methods --- p.57Chapter 3.4.1 --- Low Resolution Observations --- p.57Chapter 3.4.2 --- High Resolution Printing Results --- p.58Chapter 3.4.3 --- Analytical Comparison --- p.58Chapter 4 --- Conclusion and Future Work --- p.69Chapter 4.1 --- The Modelling of Natural Imperfections --- p.69Chapter 4.2 --- An Improved Space Filling Curve Halftoning Technique --- p.71Bibliography --- p.7