Towards Real-Time Novel View Synthesis Using Visual Hulls

This thesis discusses fast novel view synthesis from multiple images taken from different viewpoints. We propose several new algorithms that take advantage of modern graphics hardware to create novel views. Although different approaches are explored, one geometry representation, the visual hull, is employed throughout our work. First the visual hull plays an auxiliary role and assists in reconstruction of depth maps that are utilized for novel view synthesis. Then we treat the visual hull as the principal geometry representation of scene objects. A hardwareaccelerated approach is presented to reconstruct and render visual hulls directly from a set of silhouette images. The reconstruction is embedded in the rendering process and accomplished with an alpha map trimming technique. We go on by combining this technique with hardware-accelerated CSG reconstruction to improve the rendering quality of visual hulls. Finally, photometric information is exploited to overcome an inherent limitation of the visual hull. All algorithms are implemented on a distributed system. Novel views are generated at interactive or real-time frame rates.In dieser Dissertation werden mehrere Verfahren vorgestellt, mit deren Hilfe neue Ansichten einer Szene aus mehreren Bildströmen errechnet werden können. Die Bildströme werden hierzu aus unterschiedlichen Blickwinkeln auf die Szene aufgezeichnet. Wir schlagen mehrere Algorithmen vor, welche die Funktionen moderner Grafikhardware ausnutzen, um die neuen Ansichten zu errechnen. Obwohl die Verfahren sich methodisch unterscheiden, basieren sie auf der gleichen Geometriedarstellung, der Visual Hull. In der ersten Methode spielt die Visual Hull eine unterstützende Rolle bei der Rekonstruktion von Tiefenbildern, die zur Erzeugung neuer Ansichten verwendet werden. In den nachfolgend vorgestellten Verfahren dient die Visual Hull primär der Repräsentation von Objekten in einer Szene. Eine hardwarebeschleunigte Methode, um Visual Hulls direkt aus mehreren Silhouettenbildern zu rekonstruieren und zu rendern, wird vorgestellt. Das Rekonstruktionsverfahren ist hierbei Bestandteil der Renderingmethode und basiert auf einer Alpha Map Trimming Technik. Ein weiterer Algorithmus verbessert die Qualitaet der gerenderten Visual Hulls, indem das Alpha-Map-basierte Verfahren mit einer hardware-beschleunigten CSG Rekonstruktiontechnik kombiniert wird. Eine vierte Methode nutzt zusaetzlich photometrische Information aus, um eine grundlegende Beschraenkung des Visual-Hull-Ansatzes zu umgehen. Alle Verfahren ermoeglichen die interaktive oder Echtzeit- Erzeugung neuer Ansichten

Image-Based 3D Photography Using Opacity Hulls

We have built a system for acquiring and displaying high quality graphical models of objects that are impossible to scan with traditional scanners. Our system can acquire highly specular and fuzzy materials, such as fur and feathers. The hardware set-up consists of a turntable, two plasma displays, an array of cameras, and a rotating array of directional lights. We use multi-background matting techniques to acquire alpha mattes of the object from multiple viewpoints. The alpha mattes are used to construct an opacity hull. The opacity hull is a new shape representation, defined as the visual hull of the object with view-dependent opacity. It enables visualization of complex object silhouettes and seamless blending of objects into new environments. Our system also supports relighting of objects with arbitrary appearance using surface reflectance fields, a purely image-based appearance representation. Our system is the first to acquire and render surface reflectance fields under varying illumination from arbitrary viewpoints. We have built three generations of digitizers with increasing sophistication. In this paper, we present our results from digitizing hundreds of models.Engineering and Applied Science

3D-TV Production from Conventional Cameras for Sports Broadcast

3DTV production of live sports events presents a challenging problem involving conflicting requirements of main- taining broadcast stereo picture quality with practical problems in developing robust systems for cost effective deployment. In this paper we propose an alternative approach to stereo production in sports events using the conventional monocular broadcast cameras for 3D reconstruction of the event and subsequent stereo rendering. This approach has the potential advantage over stereo camera rigs of recovering full scene depth, allowing inter-ocular distance and convergence to be adapted according to the requirements of the target display and enabling stereo coverage from both existing and ‘virtual’ camera positions without additional cameras. A prototype system is presented with results of sports TV production trials for rendering of stereo and free-viewpoint video sequences of soccer and rugby

Opacity Light Fields: Interactive Rendering of Surface Light Fields with View-Dependent Opacity

We present new hardware-accelerated techniques for rendering surface light fields with opacity hulls that allow for interactive visualization of objects that have complex reflectance properties and elaborate geometrical details. The opacity hull is a shape enclosing the object with view-dependent opacity parameterized onto that shape. We call the combination of opacity hulls and surface light fields the opacity light field. Opacity light fields are ideally suited for rendering of the visually complex objects and scenes obtained with 3D photography. We show how to implement opacity light fields in the framework of three surface light field rendering methods: view-dependent texture mapping, unstructured lumigraph rendering, and light field mapping. The modified algorithms can be effectively supported on modern graphics hardware. Our results show that all three implementations are able to achieve interactive or real-time frame rates.Engineering and Applied Science

LiveCap: Real-time Human Performance Capture from Monocular Video

We present the first real-time human performance capture approach that reconstructs dense, space-time coherent deforming geometry of entire humans in general everyday clothing from just a single RGB video. We propose a novel two-stage analysis-by-synthesis optimization whose formulation and implementation are designed for high performance. In the first stage, a skinned template model is jointly fitted to background subtracted input video, 2D and 3D skeleton joint positions found using a deep neural network, and a set of sparse facial landmark detections. In the second stage, dense non-rigid 3D deformations of skin and even loose apparel are captured based on a novel real-time capable algorithm for non-rigid tracking using dense photometric and silhouette constraints. Our novel energy formulation leverages automatically identified material regions on the template to model the differing non-rigid deformation behavior of skin and apparel. The two resulting non-linear optimization problems per-frame are solved with specially-tailored data-parallel Gauss-Newton solvers. In order to achieve real-time performance of over 25Hz, we design a pipelined parallel architecture using the CPU and two commodity GPUs. Our method is the first real-time monocular approach for full-body performance capture. Our method yields comparable accuracy with off-line performance capture techniques, while being orders of magnitude faster