직접 볼륨 렌더링에서 점진적 렌즈 샘플링을 사용한 피사계 심도 렌더링

학위논문 (박사) -- 서울대학교 대학원 : 공과대학 전기·컴퓨터공학부, 2021. 2. 신영길.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.직접 볼륨 렌더링(direct volume rendering, DVR)은 측정 또는 수치 시뮬레이션으로 얻은 3차원 공간의 스칼라 필드(3D scalar fields) 데이터에서 정보를 추출하는데 널리 사용되는 기술이다. 볼륨 내부의 구조를 가시화하기 위해 복셀(voxel)의 스칼라 값은 종종 반투명의 색상으로 표현된다. 이러한 직접 볼륨 렌더링의 반투명성은 중첩된 구조 간 깊이 인식을 어렵게 한다. 깊이 인식을 향상시키기 위한 다양한 볼륨 렌더링 기법들은 주로 삽화풍 렌더링(illustrative rendering)을 기반으로 하며, 피사계 심도(depth of field, DoF) 효과와 같은 물리 기반 렌더링(physically based rendering) 기법들은 계산 시간이 오래 걸리기 때문에 적용이 어렵다. 가상 및 증강 현실과 같은 몰입형 시스템의 발전과 인간의 지각에 기반한 의료영상 시각화에 대한 관심이 증가함에 따라 직접 볼륨 렌더링에서 피사계 심도를 구현할 필요가 있다. 본 논문에서는 직접 볼륨 렌더링의 깊이 인식을 향상시키기 위해 볼륨 광선투사법에 피사계 심도 효과를 적용하는 새로운 방법을 제안한다. 픽셀 당 여러 개의 광선을 사용한 광선투사법(ray casting)을 수행하여 초점이 맞는 거리에 있는 물체는 선명하게 표현되고 초점이 맞지 않는 거리에 있는 물체는 흐리게 표현된다. 이러한 효과를 얻기 위하여 렌즈의 서로 다른 부분을 통과하는 광선들을 시뮬레이션 하는 얇은 렌즈 카메라 모델(thin lens camera model)이 사용되었다. 그리고 성능에 직접적으로 영향을 끼치는 렌즈 샘플은 최적의 렌즈 샘플링 방법을 사용하여 최소한의 개수를 가지고 앨리어싱(aliasing)이 없는 이미지를 생성하였다. 제안한 방법은 기존의 GPU 기반 볼륨 광선투사법 파이프라인 내에서 전처리 없이 구현된다. 따라서 볼륨 광선투사법의 모든 가속화 기법을 제한없이 적용할 수 있다. 또한 가속 기술로 누진 렌즈 샘플링(progressive lens sampling)을 사용하는 다중 패스 렌더링(multi-pass rendering)을 제안한다. 더 많은 렌즈 샘플들이 여러 렌더 패스들을 거치면서 점진적으로 사용된다. 각 픽셀은 착란원(circle of confusion)을 기반으로 예측된 최대 흐림 정도에 따라 다른 최종 렌더링 패스를 갖는다. 이 기법은 거리에 따른 피사계 심도 효과의 흐림 정도에 따라 각 픽셀에 다른 개수의 렌즈 샘플을 적용할 수 있게 한다. 이러한 가속화 방법은 불필요한 렌즈 샘플링을 줄이고 GPU의 캐시(cache) 적중률을 높여 직접 볼륨 렌더링에서 상호작용이 가능한 프레임 속도로 피사계 심도 효과를 렌더링 할 수 있게 한다. 다양한 데이터를 사용한 실험에서 제안한 방법은 실시간으로 사실적인 피사계 심도 효과를 생성했다. 이러한 결과는 우리의 방법이 오프라인 이미지 합성 방법과 유사한 품질의 피사계 심도 효과를 생성하면서 직접 볼륨 렌더링의 기존 피사계 심도 렌더링 방법보다 최대 12배까지 빠르다는 것을 보여준다.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

Haptic Interaction with 3D oriented point clouds on the GPU

Real-time point-based rendering and interaction with virtual objects is gaining popularity and importance as di�erent haptic devices and technologies increasingly provide the basis for realistic interaction. Haptic Interaction is being used for a wide range of applications such as medical training, remote robot operators, tactile displays and video games. Virtual object visualization and interaction using haptic devices is the main focus; this process involves several steps such as: Data Acquisition, Graphic Rendering, Haptic Interaction and Data Modi�cation. This work presents a framework for Haptic Interaction using the GPU as a hardware accelerator, and includes an approach for enabling the modi�cation of data during interaction. The results demonstrate the limits and capabilities of these techniques in the context of volume rendering for haptic applications. Also, the use of dynamic parallelism as a technique to scale the number of threads needed from the accelerator according to the interaction requirements is studied allowing the editing of data sets of up to one million points at interactive haptic frame rates

Volumetric real-time particle-based representation of large unstructured tetrahedral polygon meshes

In this paper we propose a particle-based volume rendering approach for unstructured, three-dimensional, tetrahedral polygon meshes. We stochastically generate millions of particles per second and project them on the screen in real-time. In contrast to previous rendering techniques of tetrahedral volume meshes, our method does not need a prior depth sorting of geometry. Instead, the rendered image is generated by choosing particles closest to the camera. Furthermore, we use spatial superimposing. Each pixel is constructed from multiple subpixels. This approach not only increases projection accuracy, but allows also a combination of subpixels into one superpixel that creates the well-known translucency effect of volume rendering. We show that our method is fast enough for the visualization of unstructured three-dimensional grids with hard real-time constraints and that it scales well for a high number of particles

Proxy-guided Image-based Rendering for Mobile Devices

VR headsets and hand-held devices are not powerful enough to render complex scenes in real-time. A server can take on the rendering task, but network latency prohibits a good user experience. We present a new image-based rendering (IBR) architecture for masking the latency. It runs in real-time even on very weak mobile devices, supports modern game engine graphics, and maintains high visual quality even for large view displacements. We propose a novel server-side dual-view representation that leverages an optimally-placed extra view and depth peeling to provide the client with coverage for filling disocclusion holes. This representation is directly rendered in a novel wide-angle projection with favorable directional parameterization. A new client-side IBR algorithm uses a pre-transmitted level-of-detail proxy with an encaging simplification and depth-carving to maintain highly complex geometric detail. We demonstrate our approach with typical VR / mobile gaming applications running on mobile hardware. Our technique compares favorably to competing approaches according to perceptual and numerical comparisons

Deep Bilateral Learning for Real-Time Image Enhancement

Performance is a critical challenge in mobile image processing. Given a reference imaging pipeline, or even human-adjusted pairs of images, we seek to reproduce the enhancements and enable real-time evaluation. For this, we introduce a new neural network architecture inspired by bilateral grid processing and local affine color transforms. Using pairs of input/output images, we train a convolutional neural network to predict the coefficients of a locally-affine model in bilateral space. Our architecture learns to make local, global, and content-dependent decisions to approximate the desired image transformation. At runtime, the neural network consumes a low-resolution version of the input image, produces a set of affine transformations in bilateral space, upsamples those transformations in an edge-preserving fashion using a new slicing node, and then applies those upsampled transformations to the full-resolution image. Our algorithm processes high-resolution images on a smartphone in milliseconds, provides a real-time viewfinder at 1080p resolution, and matches the quality of state-of-the-art approximation techniques on a large class of image operators. Unlike previous work, our model is trained off-line from data and therefore does not require access to the original operator at runtime. This allows our model to learn complex, scene-dependent transformations for which no reference implementation is available, such as the photographic edits of a human retoucher.Comment: 12 pages, 14 figures, Siggraph 201

Depth of field guided visualisation on light field displays

Light field displays are capable of realistic visualization of arbitrary 3D content. However, due to the finite number of light rays reproduced by the display, its bandwidth is limited in terms of angular and spatial resolution. Consequently, 3D content that falls outside of that bandwidth will cause aliasing during visualization. Therefore, a light field to be visualized must be properly preprocessed. In this thesis, we propose three methods that properly filter the parts in the input light field that would cause aliasing. First method is based on a 2D FIR circular filter that is applied over the 4D light field. Second method utilizes the structured nature of the epipolar plane images representing the light field. Third method adopts real-time multi-layer depth-of-field rendering using tiled splatting. We also establish a connection between lens parameters in the proposed depth-of-field rendering and the display’s bandwidth in order to determine the optimal blurring amount. As we prepare light field for light field displays, a stage is added to the proposed real-time rendering pipeline that simultaneously renders adjacent views. The rendering performance of the proposed methods is demonstrated on Holografika’s Holovizio 722RC projection-based light field display