A flexible and versatile studio for synchronized multi-view video recording

In recent years, the convergence of Computer Vision and Computer Graphics has put forth new research areas that work on scene reconstruction from and analysis of multi-view video footage. In free-viewpoint video, for example, new views of a scene are generated from an arbitrary viewpoint in real-time from a set of real multi-view input video streams. The analysis of real-world scenes from multi-view video to extract motion information or reflection models is another field of research that greatly benefits from high-quality input data. Building a recording setup for multi-view video involves a great effort on the hardware as well as the software side. The amount of image data to be processed is huge, a decent lighting and camera setup is essential for a naturalistic scene appearance and robust background subtraction, and the computing infrastructure has to enable real-time processing of the recorded material. This paper describes the recording setup for multi-view video acquisition that enables the synchronized recording of dynamic scenes from multiple camera positions under controlled conditions. The requirements to the room and their implementation in the separate components of the studio are described in detail. The efficiency and flexibility of the room is demonstrated on the basis of the results that we obtain with a real-time 3D scene reconstruction system, a system for non-intrusive optical motion capture and a model-based free-viewpoint video system for human actors.

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

3D Object Reconstruction using Multi-View Calibrated Images

In this study, two models are proposed, one is a visual hull model and another one is a 3D object reconstruction model. The proposed visual hull model, which is based on bounding edge representation, obtains high time performance which makes it to be one of the best methods. The main contribution of the proposed visual hull model is to provide bounding surfaces over the bounding edges, which results a complete triangular surface mesh. Moreover, the proposed visual hull model can be computed over the camera networks distributedly. The second model is a depth map based 3D object reconstruction model which results a watertight triangular surface mesh. The proposed model produces the result with acceptable accuracy as well as high completeness, only using stereo matching and triangulation. The contribution of this model is to playing with the 3D points to find the best reliable ones and fitting a surface over them

Grimage: markerless 3D interactions

International audienceGrimage glues multi-camera 3D modeling, physical simulation and parallel execution for a new immersive experience. Put your hands or any object into the interaction space. It is instantaneously modeled in 3D and injected into a virtual world populated with solid and soft objects. Push them, catch them and squeeze them

Scalable 3D video of dynamic scenes

In this paper we present a scalable 3D video framework for capturing and rendering dynamic scenes. The acquisition system is based on multiple sparsely placed 3D video bricks, each comprising a projector, two grayscale cameras, and a color camera. Relying on structured light with complementary patterns, texture images and pattern-augmented views of the scene are acquired simultaneously by time-multiplexed projections and synchronized camera exposures. Using space-time stereo on the acquired pattern images, high-quality depth maps are extracted, whose corresponding surface samples are merged into a view-independent, point-based 3D data structure. This representation allows for effective photo-consistency enforcement and outlier removal, leading to a significant decrease of visual artifacts and a high resulting rendering quality using EWA volume splatting. Our framework and its view-independent representation allow for simple and straightforward editing of 3D video. In order to demonstrate its flexibility, we show compositing techniques and spatiotemporal effect