273,951 research outputs found
์ง์ ๋ณผ๋ฅจ ๋ ๋๋ง์์ ์ ์ง์ ๋ ์ฆ ์ํ๋ง์ ์ฌ์ฉํ ํผ์ฌ๊ณ ์ฌ๋ ๋ ๋๋ง
ํ์๋
ผ๋ฌธ (๋ฐ์ฌ) -- ์์ธ๋ํ๊ต ๋ํ์ : ๊ณต๊ณผ๋ํ ์ ๊ธฐยท์ปดํจํฐ๊ณตํ๋ถ, 2021. 2. ์ ์๊ธธ.Direct volume rendering is a widely used technique for extracting information from 3D scalar fields acquired by measurement or numerical simulation. To visualize the structure inside the volume, the voxels scalar value is often represented by a translucent color. This translucency of direct volume rendering makes it difficult to perceive the depth between the nested structures. Various volume rendering techniques to improve depth perception are mainly based on illustrative rendering techniques, and physically based rendering techniques such as depth of field effects are difficult to apply due to long computation time. With the development of immersive systems such as virtual and augmented reality and the growing interest in perceptually motivated medical visualization, it is necessary to implement depth of field in direct volume rendering.
This study proposes a novel method for applying depth of field effects to volume ray casting to improve the depth perception. By performing ray casting using multiple rays per pixel, objects at a distance in focus are sharply rendered and objects at an out-of-focus distance are blurred. To achieve these effects, a thin lens camera model is used to simulate rays passing through different parts of the lens. And an effective lens sampling method is used to generate an aliasing-free image with a minimum number of lens samples that directly affect performance. The proposed method is implemented without preprocessing based on the GPU-based volume ray casting pipeline. Therefore, all acceleration techniques of volume ray casting can be applied without restrictions.
We also propose multi-pass rendering using progressive lens sampling as an acceleration technique. More lens samples are progressively used for ray generation over multiple render passes. Each pixel has a different final render pass depending on the predicted maximum blurring size based on the circle of confusion. This technique makes it possible to apply a different number of lens samples for each pixel, depending on the degree of blurring of the depth of field effects over distance. This acceleration method reduces unnecessary lens sampling and increases the cache hit rate of the GPU, allowing us to generate the depth of field effects at interactive frame rates in direct volume rendering.
In the experiments using various data, the proposed method generated realistic depth of field effects in real time. These results demonstrate that our method produces depth of field effects with similar quality to the offline image synthesis method and is up to 12 times faster than the existing depth of field method in direct volume rendering.์ง์ ๋ณผ๋ฅจ ๋ ๋๋ง(direct volume rendering, DVR)์ ์ธก์ ๋๋ ์์น ์๋ฎฌ๋ ์ด์
์ผ๋ก ์ป์ 3์ฐจ์ ๊ณต๊ฐ์ ์ค์นผ๋ผ ํ๋(3D scalar fields) ๋ฐ์ดํฐ์์ ์ ๋ณด๋ฅผ ์ถ์ถํ๋๋ฐ ๋๋ฆฌ ์ฌ์ฉ๋๋ ๊ธฐ์ ์ด๋ค. ๋ณผ๋ฅจ ๋ด๋ถ์ ๊ตฌ์กฐ๋ฅผ ๊ฐ์ํํ๊ธฐ ์ํด ๋ณต์
(voxel)์ ์ค์นผ๋ผ ๊ฐ์ ์ข
์ข
๋ฐํฌ๋ช
์ ์์์ผ๋ก ํํ๋๋ค. ์ด๋ฌํ ์ง์ ๋ณผ๋ฅจ ๋ ๋๋ง์ ๋ฐํฌ๋ช
์ฑ์ ์ค์ฒฉ๋ ๊ตฌ์กฐ ๊ฐ ๊น์ด ์ธ์์ ์ด๋ ต๊ฒ ํ๋ค. ๊น์ด ์ธ์์ ํฅ์์ํค๊ธฐ ์ํ ๋ค์ํ ๋ณผ๋ฅจ ๋ ๋๋ง ๊ธฐ๋ฒ๋ค์ ์ฃผ๋ก ์ฝํํ ๋ ๋๋ง(illustrative rendering)์ ๊ธฐ๋ฐ์ผ๋ก ํ๋ฉฐ, ํผ์ฌ๊ณ ์ฌ๋(depth of field, DoF) ํจ๊ณผ์ ๊ฐ์ ๋ฌผ๋ฆฌ ๊ธฐ๋ฐ ๋ ๋๋ง(physically based rendering) ๊ธฐ๋ฒ๋ค์ ๊ณ์ฐ ์๊ฐ์ด ์ค๋ ๊ฑธ๋ฆฌ๊ธฐ ๋๋ฌธ์ ์ ์ฉ์ด ์ด๋ ต๋ค. ๊ฐ์ ๋ฐ ์ฆ๊ฐ ํ์ค๊ณผ ๊ฐ์ ๋ชฐ์
ํ ์์คํ
์ ๋ฐ์ ๊ณผ ์ธ๊ฐ์ ์ง๊ฐ์ ๊ธฐ๋ฐํ ์๋ฃ์์ ์๊ฐํ์ ๋ํ ๊ด์ฌ์ด ์ฆ๊ฐํจ์ ๋ฐ๋ผ ์ง์ ๋ณผ๋ฅจ ๋ ๋๋ง์์ ํผ์ฌ๊ณ ์ฌ๋๋ฅผ ๊ตฌํํ ํ์๊ฐ ์๋ค.
๋ณธ ๋
ผ๋ฌธ์์๋ ์ง์ ๋ณผ๋ฅจ ๋ ๋๋ง์ ๊น์ด ์ธ์์ ํฅ์์ํค๊ธฐ ์ํด ๋ณผ๋ฅจ ๊ด์ ํฌ์ฌ๋ฒ์ ํผ์ฌ๊ณ ์ฌ๋ ํจ๊ณผ๋ฅผ ์ ์ฉํ๋ ์๋ก์ด ๋ฐฉ๋ฒ์ ์ ์ํ๋ค. ํฝ์
๋น ์ฌ๋ฌ ๊ฐ์ ๊ด์ ์ ์ฌ์ฉํ ๊ด์ ํฌ์ฌ๋ฒ(ray casting)์ ์ํํ์ฌ ์ด์ ์ด ๋ง๋ ๊ฑฐ๋ฆฌ์ ์๋ ๋ฌผ์ฒด๋ ์ ๋ช
ํ๊ฒ ํํ๋๊ณ ์ด์ ์ด ๋ง์ง ์๋ ๊ฑฐ๋ฆฌ์ ์๋ ๋ฌผ์ฒด๋ ํ๋ฆฌ๊ฒ ํํ๋๋ค. ์ด๋ฌํ ํจ๊ณผ๋ฅผ ์ป๊ธฐ ์ํ์ฌ ๋ ์ฆ์ ์๋ก ๋ค๋ฅธ ๋ถ๋ถ์ ํต๊ณผํ๋ ๊ด์ ๋ค์ ์๋ฎฌ๋ ์ด์
ํ๋ ์์ ๋ ์ฆ ์นด๋ฉ๋ผ ๋ชจ๋ธ(thin lens camera model)์ด ์ฌ์ฉ๋์๋ค. ๊ทธ๋ฆฌ๊ณ ์ฑ๋ฅ์ ์ง์ ์ ์ผ๋ก ์ํฅ์ ๋ผ์น๋ ๋ ์ฆ ์ํ์ ์ต์ ์ ๋ ์ฆ ์ํ๋ง ๋ฐฉ๋ฒ์ ์ฌ์ฉํ์ฌ ์ต์ํ์ ๊ฐ์๋ฅผ ๊ฐ์ง๊ณ ์จ๋ฆฌ์ด์ฑ(aliasing)์ด ์๋ ์ด๋ฏธ์ง๋ฅผ ์์ฑํ์๋ค. ์ ์ํ ๋ฐฉ๋ฒ์ ๊ธฐ์กด์ GPU ๊ธฐ๋ฐ ๋ณผ๋ฅจ ๊ด์ ํฌ์ฌ๋ฒ ํ์ดํ๋ผ์ธ ๋ด์์ ์ ์ฒ๋ฆฌ ์์ด ๊ตฌํ๋๋ค. ๋ฐ๋ผ์ ๋ณผ๋ฅจ ๊ด์ ํฌ์ฌ๋ฒ์ ๋ชจ๋ ๊ฐ์ํ ๊ธฐ๋ฒ์ ์ ํ์์ด ์ ์ฉํ ์ ์๋ค.
๋ํ ๊ฐ์ ๊ธฐ์ ๋ก ๋์ง ๋ ์ฆ ์ํ๋ง(progressive lens sampling)์ ์ฌ์ฉํ๋ ๋ค์ค ํจ์ค ๋ ๋๋ง(multi-pass rendering)์ ์ ์ํ๋ค. ๋ ๋ง์ ๋ ์ฆ ์ํ๋ค์ด ์ฌ๋ฌ ๋ ๋ ํจ์ค๋ค์ ๊ฑฐ์น๋ฉด์ ์ ์ง์ ์ผ๋ก ์ฌ์ฉ๋๋ค. ๊ฐ ํฝ์
์ ์ฐฉ๋์(circle of confusion)์ ๊ธฐ๋ฐ์ผ๋ก ์์ธก๋ ์ต๋ ํ๋ฆผ ์ ๋์ ๋ฐ๋ผ ๋ค๋ฅธ ์ต์ข
๋ ๋๋ง ํจ์ค๋ฅผ ๊ฐ๋๋ค. ์ด ๊ธฐ๋ฒ์ ๊ฑฐ๋ฆฌ์ ๋ฐ๋ฅธ ํผ์ฌ๊ณ ์ฌ๋ ํจ๊ณผ์ ํ๋ฆผ ์ ๋์ ๋ฐ๋ผ ๊ฐ ํฝ์
์ ๋ค๋ฅธ ๊ฐ์์ ๋ ์ฆ ์ํ์ ์ ์ฉํ ์ ์๊ฒ ํ๋ค. ์ด๋ฌํ ๊ฐ์ํ ๋ฐฉ๋ฒ์ ๋ถํ์ํ ๋ ์ฆ ์ํ๋ง์ ์ค์ด๊ณ GPU์ ์บ์(cache) ์ ์ค๋ฅ ์ ๋์ฌ ์ง์ ๋ณผ๋ฅจ ๋ ๋๋ง์์ ์ํธ์์ฉ์ด ๊ฐ๋ฅํ ํ๋ ์ ์๋๋ก ํผ์ฌ๊ณ ์ฌ๋ ํจ๊ณผ๋ฅผ ๋ ๋๋ง ํ ์ ์๊ฒ ํ๋ค.
๋ค์ํ ๋ฐ์ดํฐ๋ฅผ ์ฌ์ฉํ ์คํ์์ ์ ์ํ ๋ฐฉ๋ฒ์ ์ค์๊ฐ์ผ๋ก ์ฌ์ค์ ์ธ ํผ์ฌ๊ณ ์ฌ๋ ํจ๊ณผ๋ฅผ ์์ฑํ๋ค. ์ด๋ฌํ ๊ฒฐ๊ณผ๋ ์ฐ๋ฆฌ์ ๋ฐฉ๋ฒ์ด ์คํ๋ผ์ธ ์ด๋ฏธ์ง ํฉ์ฑ ๋ฐฉ๋ฒ๊ณผ ์ ์ฌํ ํ์ง์ ํผ์ฌ๊ณ ์ฌ๋ ํจ๊ณผ๋ฅผ ์์ฑํ๋ฉด์ ์ง์ ๋ณผ๋ฅจ ๋ ๋๋ง์ ๊ธฐ์กด ํผ์ฌ๊ณ ์ฌ๋ ๋ ๋๋ง ๋ฐฉ๋ฒ๋ณด๋ค ์ต๋ 12๋ฐฐ๊น์ง ๋น ๋ฅด๋ค๋ ๊ฒ์ ๋ณด์ฌ์ค๋ค.CHAPTER 1 INTRODUCTION 1
1.1 Motivation 1
1.2 Dissertation Goals 5
1.3 Main Contributions 6
1.4 Organization of Dissertation 8
CHAPTER 2 RELATED WORK 9
2.1 Depth of Field on Surface Rendering 10
2.1.1 Object-Space Approaches 11
2.1.2 Image-Space Approaches 15
2.2 Depth of Field on Volume Rendering 26
2.2.1 Blur Filtering on Slice-Based Volume Rendering 28
2.2.2 Stochastic Sampling on Volume Ray Casting 30
CHAPTER 3 DEPTH OF FIELD VOLUME RAY CASTING 33
3.1 Fundamentals 33
3.1.1 Depth of Field 34
3.1.2 Camera Models 36
3.1.3 Direct Volume Rendering 42
3.2 Geometry Setup 48
3.3 Lens Sampling Strategy 53
3.3.1 Sampling Techniques 53
3.3.2 Disk Mapping 57
3.4 CoC-Based Multi-Pass Rendering 60
3.4.1 Progressive Lens Sample Sequence 60
3.4.2 Final Render Pass Determination 62
CHAPTER 4 GPU IMPLEMENTATION 66
4.1 Overview 66
4.2 Rendering Pipeline 67
4.3 Focal Plane Transformation 74
4.4 Lens Sample Transformation 76
CHAPTER 5 EXPERIMENTAL RESULTS 78
5.1 Number of Lens Samples 79
5.2 Number of Render Passes 82
5.3 Render Pass Parameter 84
5.4 Comparison with Previous Methods 87
CHAPTER 6 CONCLUSION 97
Bibliography 101
Appendix 111Docto
Pressure-induced densification of vitreous silica: insight from elastic properties
\textit{In situ} high-pressure Brillouin light scattering experiments along
loading-unloading paths are used to investigate the compressibility of vitreous
silica. An accurate equation of state is obtained below \SI{9}{GPa} using sound
velocities corrected for dispersion. Conversely, huge inelastic effects are
observed in the range \SIrange{10}{60}{GPa}, unveiling the reversible
transformation from the fourfold-coordinated structure to the sixfold one. We
find that the associated density changes fully correlate with the average Si
coordination number. Decompression curves from above \SI{20}{GPa} reveal abrupt
backward coordination changes around \SIrange{10}{15}{GPa} and significant
hysteresis. Further, contrary to common wisdom, the residual densification of
recovered silica samples can be figured out from the pressure cycles.Comment: 5 pages, 4 figures, revised versio
Strain localization and anisotropic correlations in a mesoscopic model of amorphous plasticity
A mesoscopic model for shear plasticity of amorphous materials in two
dimensions is introduced, and studied through numerical simulations in order to
elucidate the macroscopic (large scale) mechanical behavior. Plastic
deformation is assumed to occur through a series of local reorganizations.
Using a discretization of the mechanical fields on a discrete lattice, local
reorganizations are modeled as local slip events. Local yield stresses are
randomly distributed in space and invariant in time. Each plastic slip event
induces a long-ranged elastic stress redistribution. Rate and thermal effects
are not discussed in the present study. Extremal dynamics allows for recovering
many of the complex features of amorphous plasticity observed experimentally
and in numerical atomistic simulations in the quasi-static regime. In
particular, a quantitative picture of localization, and of the anisotropic
strain correlation both in the initial transient regime, and in the steady
state are provided. In addition, the preparation of the amorphous sample is
shown to have a crucial effect of on the localization behavior
Strain localization and anisotropic correlations in a mesoscopic model of amorphous plasticity
A mesoscopic model for shear plasticity of amorphous materials in two
dimensions is introduced, and studied through numerical simulations in order to
elucidate the macroscopic (large scale) mechanical behavior. Plastic
deformation is assumed to occur through a series of local reorganizations.
Using a discretization of the mechanical fields on a discrete lattice, local
reorganizations are modeled as local slip events. Local yield stresses are
randomly distributed in space and invariant in time. Each plastic slip event
induces a long-ranged elastic stress redistribution. Rate and thermal effects
are not discussed in the present study. Extremal dynamics allows for recovering
many of the complex features of amorphous plasticity observed experimentally
and in numerical atomistic simulations in the quasi-static regime. In
particular, a quantitative picture of localization, and of the anisotropic
strain correlation both in the initial transient regime, and in the steady
state are provided. In addition, the preparation of the amorphous sample is
shown to have a crucial effect of on the localization behavior
A new class of low compressibility materials: Clathrates of silicon and related materials
We discuss the high pressure properties of different silicon clathrate structures that we have investigated by means of X-ray diffraction and ab initio calculations. Compressibility transition pressures or phase transformations are interpreted as a function of the nature of the guest atom intercalation, The compressibility of the clathrate structure is in all cases close to that of silicon diamond whereas transition pressures or the high pressure phases are extremely depending on the nature of the guest atom. We address the implications for obtaining a metallic material as hard as diamond
Thermogravimetry and neutron thermodiffractometry studies of the H-YBa2Cu3O7 system.
The high Tc superconducting oxide YBa2Cu3O7ยฟx reacts with hydrogen gas. Thermogravimetric, X-ray and neutron scattering experiments allow us to propose a two-step type of hydrogen bonding. Firstly, a few hydrogen atoms fill some oxygen vacancies and may favourably modify the electron state, giving rise to a slight increase in the critical temperature. Secondly, after a prolonged heating period, the collapse of the YBa2Cu3O7ยฟx type framework and of superconductivity were observed, and a new, highly hydrogenated material appeared
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