Many-Light Real-Time Global Illumination using Sparse Voxel Octree

Global illumination (GI) rendering simulates the propagation of light through a 3D volume and its interaction with surfaces, dramatically increasing the fidelity of computer generated images. While off-line GI algorithms such as ray tracing and radiosity can generate physically accurate images, their rendering speeds are too slow for real-time applications. The many-light method is one of many novel emerging real-time global illumination algorithms. However, it requires many shadow maps to be generated for Virtual Point Light (VPL) visibility tests, which reduces its efficiency. Prior solutions restrict either the number or accuracy of shadow map updates, which may lower the accuracy of indirect illumination or prevent the rendering of fully dynamic scenes. In this thesis, we propose a hybrid real-time GI algorithm that utilizes an efficient Sparse Voxel Octree (SVO) ray marching algorithm for visibility tests instead of the shadow map generation step of the many-light algorithm. Our technique achieves high rendering fidelity at about 50 FPS, is highly scalable and can support thousands of VPLs generated on the fly. A survey of current real-time GI techniques as well as details of our implementation using OpenGL and Shader Model 5 are also presented

Weakly supervised 3D Reconstruction with Adversarial Constraint

Supervised 3D reconstruction has witnessed a significant progress through the use of deep neural networks. However, this increase in performance requires large scale annotations of 2D/3D data. In this paper, we explore inexpensive 2D supervision as an alternative for expensive 3D CAD annotation. Specifically, we use foreground masks as weak supervision through a raytrace pooling layer that enables perspective projection and backpropagation. Additionally, since the 3D reconstruction from masks is an ill posed problem, we propose to constrain the 3D reconstruction to the manifold of unlabeled realistic 3D shapes that match mask observations. We demonstrate that learning a log-barrier solution to this constrained optimization problem resembles the GAN objective, enabling the use of existing tools for training GANs. We evaluate and analyze the manifold constrained reconstruction on various datasets for single and multi-view reconstruction of both synthetic and real images

Rendering of light shaft and shadow for indoor environments enhancing technique

The ray marching methods have become the most attractive method to provide realism in rendering the effects of light scattering in the participating media of numerous applications. This has attracted significant attention from the scientific community. Up-sampling of ray marching methods is suitable to evaluate light scattering effects such as volumetric shadows and light shafts for rendering realistic scenes, but suffers of cost a lot for rendering. Therefore, some encouraging outcomes have been achieved by using down-sampling of ray marching approach to accelerate rendered scenes. However, these methods are inherently prone to artifacts, aliasing and incorrect boundaries due to the reduced number of sample points along view rays. This study proposed a new enhancing technique to render light shafts and shadows taking into consideration the integration light shafts, volumetric shadows, and shadows for indoor environments. This research has three major phases that cover species of the effects addressed in this thesis. The first phase includes the soft volumetric shadows creation technique called Soft Bilateral Filtering Volumetric Shadows (SoftBiF-VS). The soft shadow was created using a new algorithm called Soft Bilateral Filtering Shadow (SBFS). This technique was started by developing an algorithm called Imperfect Multi-View Soft Shadows (IMVSSs) based on down-sampling multiple point lights (DMPLs) and multiple depth maps, which are processed by using bilateral filtering to obtain soft shadows. Then, down-sampling light scattering model was used with (SBFS) to create volumetric shadows, which was improved using cross-bilateral filter to get soft volumetric shadows. In the second phase, soft light shaft was generated using a new technique called Realistic Real-Time Soft Bilateral Filtering Light Shafts (realTiSoftLS). This technique computed the light shaft depending on down-sampling volumetric light model and depth test, and was interpolated by bilateral filtering to gain soft light shafts. Finally, an enhancing technique for integrating all of these effects that represent the third phase of this research was achieved. The performance of the new enhanced technique was evaluated quantitatively and qualitatively a measured using standard dataset. Results from the experiment showed that 63% of the participants gave strong positive responses to this technique of improving realism. From the quantitative evaluation, the results revealed that the technique has dramatically outpaced the stateof- the-art techniques with a speed of 74 fps in improving the performance for indoor environments

Photon Splatting Using a View-Sample Cluster Hierarchy

Splatting photons onto primary view samples, rather than gathering from a photon acceleration structure, can be a more efficient approach to evaluating the photon-density estimate in interactive applications, where the number of photons is often low compared to the number of view samples. Most photon splatting approaches struggle with large photon radii or high resolutions due to overdraw and insufficient culling. In this paper, we show how dynamic real-time diffuse interreflection can be achieved by using a full 3D acceleration structure built over the view samples and then splatting photons onto the view samples by traversing this data structure. Full dynamic lighting and scenes are possible by tracing and splatting photons, and rebuilding the acceleration structure every frame. We show that the number of view-sample/photon tests can be significantly reduced and suggest further culling techniques based on the normal cone of each node in the hierarchy. Finally, we present an approximate variant of our algorithm where photon traversal is stopped at a fixed level of our hierarchy, and the incoming radiance is accumulated per node and direction, rather than per view sample. This improves performance significantly with little visible degradation of quality

On sparse voxel DAGs and memory efficient compression of surface attributes for real-time scenarios

The general shape of a 3D object can expeditiously be represented as, e.g., triangles or voxels, while smaller-scale features usually are parameterized over the surface of the object. Such features include, but are not limited to, color details, small-scale surface-normal variations, or even view-dependent properties required for the light-surface interactions. This thesis is a collection of four papers that focus on new ways to compress and efficiently utilize surface data in 3D for real-time usage.In Paper IA and IB, we extend upon the concept of sparse voxel DAGs, a real-time compression format of a voxel-grid, to allow an attribute mapping with a negligible impact on the size. The main contribution, however, is a novel real-time compression format of the mapped colors over such sparse voxel surfaces.Paper II aims to utilize the results of the previous papers to achieve uv-free texturing of surfaces, such as triangle meshes, with optimized run-time minification as well as magnification filtering.Paper III extends upon previous compact representations of view dependent radiance using spherical gaussians (SG). By using a convolutional neural network, we are able to compress the light-field by finding SGs with free directions, amplitudes and sharpnesses, whereas previous methods were limited to only free amplitudes in similar scenarios

Optimizing computed tomography : quality assurance, radiation dose and contrast media

Computed tomography (CT) is an important modality in radiology; it enables imaging of the inside of patients without superimposed anatomy. The radiation dose and quality of a CT image are highly dependent on the CT scanner, the scan settings and, if applicable, the timing and dosage of the intravenous contrast media (CM). The aim of this Thesis was to develop tools and insights that help maximize the value of examinations for patients undergoing CT and to reduce its cost in terms of radiation and CM dose. The Thesis consists of five studies. The first paper was on quality control (QC) of CT, which is the foundation for a radiology clinic: it provides trust that the equipment functions as expected. A new method of performing routine QCs was proposed where the concept of key performance indicators (KPI) was introduced, together with a semi-automatic process allowing for daily QCs. During the time of the study, multiple deviations were discovered that would have been difficult to detect using traditional QCs. Performing QCs more frequently facilitates more extensive trend analysis. The second paper was on automatic tube current modulation (ATCM). A phantom and a method for the characterization of ATCM were developed. These allowed for a characterization of CT scanners from the four main CT vendors in Sweden, summarized in four extensive tables showing how the ATCM responds to changes in scan parameters. More specifically, the tables present how changes in scan settings of the localizer radiograph (LR), scan settings of the acquisition, reconstruction parameters and patient miscentering affect the ATCM. The third paper was on radiation dose estimation uncertainties coupled to the patient table. In most commercial radiation dose estimation software packages for CT, the patient table is not included. That effect was previously unknown but could be shown using Monte Carlo (MC) calculations of CT scans performed with and without the patient table. It was shown that by not including the effect from the patient table in radiation dose estimations, the radiation doses are overestimated by 5% to 23%, depending on the scan mode. The fourth paper evaluated whether the standard LR can be replaced by a low-dose spiral scan, a so-called synthetic LR (SLR). Such an SLR can potentially improve ATCM, CM dosage and CT planning. Radiation doses were estimated using MC, the image quality was compared in a prospective study of ten patients and the impact of miscentering was investigated with a phantom measurement of water equivalent diameters. It was shown that the radiation doses and the image quality of SLR and LRs were similar. Estimated water equivalent diameters were more consistent when calculated from the low-dose spiral scan compared to the LRs. It was concluded that it is feasible to replace the traditional LR with an SLR for CT scan planning. The fifth paper was a continued investigation of the low-dose spiral scan, but with focus on intravenous CM dosage planning. Altogether, 238 patients who had undergone PET/CT and ii for whom body metrics (height and weight) had been acquired were retrospectively analyzed, the CT number enhancement of the liver was measured, and body volumes of muscle and fat were calculated using the attenuation correction CT (low-dose spiral scan). Multiple linear regressions showed that for CM dose planning, the body volumes of muscle and fat are better to use than body weight. However, the adjusted R2 values of all the investigated models were low, indicating that responses to CM dosage are complex and require more research. In this PhD Thesis, tools and insights were developed to improve the imaging stability of the CT scan by developing semi-automatic QC protocols and techniques to better estimate patient size and shape potentially reducing variation in image quality, radiation dose and CM enhancement among patients

Collimated Whole Volume Light Scattering in Homogeneous Finite Media

Crepuscular rays form when light encounters an optically thick or opaque medium which masks out portions of the visible scene. Real-time applications commonly estimate this phenomena by connecting paths between light sources and the camera after a single scattering event. We provide a set of algorithms for solving integration and sampling of single-scattered collimated light in a box-shaped medium and show how they extend to multiple scattering and convex media. First, a method for exactly integrating the unoccluded single scattering in rectilinear box-shaped medium is proposed and paired with a ratio estimator and moment-based approximation. Compared to previous methods, it requires only a single sample in unoccluded areas to compute the whole integral solution and provides greater convergence in the rest of the scene. Second, we derive an importance sampling scheme accounting for the entire geometry of the medium. This sampling strategy is then incorporated in an optimized Monte Carlo integration. The resulting integration scheme yields visible noise reduction and it is directly applicable to indoor scene rendering in room-scale interactive experiences. Furthermore, it extends to multiple light sources and achieves superior converge compared to independent sampling with existing algorithms. We validate our techniques against previous methods based on ray marching and distance sampling to prove their superior noise reduction capability

The delta radiance field

The wide availability of mobile devices capable of computing high fidelity graphics in real-time has sparked a renewed interest in the development and research of Augmented Reality applications. Within the large spectrum of mixed real and virtual elements one specific area is dedicated to produce realistic augmentations with the aim of presenting virtual copies of real existing objects or soon to be produced products. Surprisingly though, the current state of this area leaves much to be desired: Augmenting objects in current systems are often presented without any reconstructed lighting whatsoever and therefore transfer an impression of being glued over a camera image rather than augmenting reality. In light of the advances in the movie industry, which has handled cases of mixed realities from one extreme end to another, it is a legitimate question to ask why such advances did not fully reflect onto Augmented Reality simulations as well. Generally understood to be real-time applications which reconstruct the spatial relation of real world elements and virtual objects, Augmented Reality has to deal with several uncertainties. Among them, unknown illumination and real scene conditions are the most important. Any kind of reconstruction of real world properties in an ad-hoc manner must likewise be incorporated into an algorithm responsible for shading virtual objects and transferring virtual light to real surfaces in an ad-hoc fashion. The immersiveness of an Augmented Reality simulation is, next to its realism and accuracy, primarily dependent on its responsiveness. Any computation affecting the final image must be computed in real-time. This condition rules out many of the methods used for movie production. The remaining real-time options face three problems: The shading of virtual surfaces under real natural illumination, the relighting of real surfaces according to the change in illumination due to the introduction of a new object into a scene, and the believable global interaction of real and virtual light. This dissertation presents contributions to answer the problems at hand. Current state-of-the-art methods build on Differential Rendering techniques to fuse global illumination algorithms into AR environments. This simple approach has a computationally costly downside, which limits the options for believable light transfer even further. This dissertation explores new shading and relighting algorithms built on a mathematical foundation replacing Differential Rendering. The result not only presents a more efficient competitor to the current state-of-the-art in global illumination relighting, but also advances the field with the ability to simulate effects which have not been demonstrated by contemporary publications until now

Gerçek zamanlı sahnelerin ışıklandırılmasına yardımcı, dinamik voxelleştirme teknikleri.

In this thesis, we focus on approximating indirect illumination on real-time applications to visualize realistic scenes. In order to approximate indirect illumination we provide a fast sparse voxel tree structure for highly dynamic scenes. Our system tries to cover traditional real-time animation methods including dynamic non-deforming objects and objects that deform with bone transformations. The voxel scene data structure is designed for fully dynamic objects and eliminates the voxelization of the dynamic objects per frame which in turn facilitates efficient realistic rendering. We combine this new scene information structure with the widely used real-time rendering techniques and these techniques’ data structures such as shadow mapping and deferred rendering to provide an efficient cone ray-casting algorithm that achieves global illumination in real-time. M.S. - Master of Scienc