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This article describes an investigation of interactive narrative in virtual reality (VR) through Samuel Beckett's theatrical text Play. Actors are captured in a green screen environment using free-viewpoint video (FVV). Built in a game engine, the scene is complete with binaural spatial audio and six degrees of freedom of movement. The project explores how ludic qualities in the original text elicit the conversational and interactive specificities of the digital medium. The work affirms potential for interactive narrative in VR, opens new experiences of the text and highlights the reorganization of the author-audience dynamic.

The following work presents a self-regulating filter that is capable of performing accurate upsampling of dynamic point cloud data sequences captured using wide-baseline multi-view camera setups. This is achieved by using two-way temporal projection of edge-aware upsampled point clouds while imposing coherence and noise filtering via a windowed, self-regulating noise filter. We use a state of the art Spatio-Temporal Edge-Aware scene flow estimation to accurately model the motion of points across a sequence and then, leveraging the spatio-temporal inconsistency of unstructured noise, we perform a weighted Hausdorff distance-based noise filter over a given window. Our results demonstrate that this approach produces temporally coherent, upsampled point clouds while mitigating both additive and unstructured noise. In addition to filtering noise, the algorithm is able to greatly reduce intermittent loss of pertinent geometry. The system performs well in dynamic real world scenarios with both stationary and non-stationary cameras as well as synthetically rendered environments for baseline study.

We present a method for augmenting hand-drawn characters and creatures with global illumination effects. Given a single view drawing only, we use a novel CNN to predict a high-quality normal map of the same resolution. The predicted normals are then used as guide to inflate a surface into a 3D proxy mesh visually consistent and suitable to augment the input 2D art with convincing global illumination effects while keeping the hand-drawn look and feel. Along with this paper, a new high resolution dataset of line drawings with corresponding ground-truth normal and depth maps will be shared. We validate our CNN, comparing our neural predictions qualitatively and quantitatively with the recent state-of-the art, show results for various hand-drawn images and animations, and compare with alternative modeling approaches.

We present a scalable pipeline for Free-Viewpoint Video (FVV) content creation, considering also visualisation in Augmented Reality (AR) and Virtual Reality (VR). We support a range of scenarios where there may be a limited number of handheld consumer cameras, but also demonstrate how our method can be applied in professional multi-camera setups. Our novel pipeline extends many state-of-the-art techniques (such as structure-from-motion, shape-from-silhouette and multi-view stereo) and incorporates bio-mechanical constraints through 3D skeletal information as well as efficient camera pose estimation algorithms. We introduce multi-source shape-from-silhouette (MS-SfS) combined with fusion of different geometry data as crucial components for accurate reconstruction in sparse camera settings. Our approach is highly flexible and our results indicate suitability either for affordable content creation for VR/AR or for interactive FVV visualisation where a user can choose an arbitrary viewpoint or sweep between known views using view synthesis.

We present a semi-automatic method for creating shades and self-shadows in cel animation. Besides producing attractive images, shades and shadows provide important visual cues about depth, shapes, movement and lighting of the scene. In conventional cel animation, shades and shadows are drawn by hand. As opposed to previous approaches, this method does not rely on a complex 3D reconstruction of the scene: its key advantages are simplicity and ease of use. The tool was designed to stay as close as possible to the natural 2D creative environment and therefore provides an intuitive and user-friendly interface. Our system creates shading based on hand-drawn objects or characters, given very limited guidance from the user. The method employs simple yet very efficient algorithms to create shading directly out of drawn strokes. We evaluate our system through a subjective user study and provide qualitative comparison of our method versus existing professional tools and state of the art.

This poster describes a reinterpretation of Samuel Beckett's theatrical text Play for virtual reality (VR). It is an aesthetic reflection on practice that follows up an a technical project description submitted to ISMAR 2017 [O'Dwyer et al. 2017]. Actors are captured in a green screen environment using free-viewpoint video (FVV) techniques, and the scene is built in a game engine, complete with binaural spatial audio and six degrees of freedom of movement. The project explores how ludic qualities in the original text help elicit the conversational and interactive specificities of the digital medium. The work affirms the potential for interactive narrative in VR, opens new experiences of the text, and highlights the reorganisation of the author-audience dynamic.

This demo paper describes a project that engages cutting-edge free viewpoint video (FVV) techniques for developing content for an augmented reality prototype. The article traces the evolutionary process from concept, through narrative development, to completed AR prototypes for the HoloLens and handheld mobile devices. It concludes with some reflections on the affordances of the various hardware formats and posits future directions for the research.

Since the early years of the twenty-first century, the performing arts have been party to an increasing number of digital media projects that bring renewed attention to questions about, on one hand, new working processes involving capture and distribution techniques, and on the other hand, how particular works—with bespoke hard and software—can exert an efficacy over how work is created by the artist/producer or received by the audience. The evolution of author/audience criteria demand that digital arts practice modify aesthetic and storytelling strategies, to types that are more appropriate to communicating ideas over interactive digital networks, wherein AR/VR technologies are rapidly becoming the dominant interface. This project explores these redefined criteria through a reimagining of Samuel Becketts Play (1963) for digital culture. This paper offers an account of the working processes, the aesthetic and technical considerations that guide artistic decisions and how we attempt to place the overall work in the state of the art.

We present a simulation framework for a 3-D high-resolution imaging radar at 300 GHz with mechanical scanning. This tool allows us to reproduce the imaging capabilities of the radar in different setups and with different targets. The simulations are based on a ray-tracing approximation combined with a bidirectional reflectance distribution function (BRDF) model for the scattering of rough surfaces. Moreover, we present a novel approach to estimate the scattering parameters of the BRDF model for different types of targets from the combination of the radar data and information obtained from an infrared structure light sensor. This new framework will serve as a baseline for the design of future radar multistatic configurations and to generate synthetic data to train automatic target recognition algorithms.

In the context of 3D reconstruction, we present a static multi-texturing system yielding a seamless texture atlas calculated by combining the colour information from several photos from the same subject covering most of its surface. These pictures can be provided by shooting just one camera several times when reconstructing a static object, or a set of synchronized cameras, when dealing with a human or any other moving object. We suppress the colour seams due to image misalignments and irregular lighting conditions that multi-texturing approaches typically suffer from, while minimizing the blurring effect introduced by colour blending techniques. Our system is robust enough to compensate for the almost inevitable inaccuracies of 3D meshes obtained with visual hull-based techniques: errors in silhouette segmentation, inherently bad handling of concavities, etc.

The present paper presents a fully automatic low-cost system for generating animatable and statically multi-textured avatars of real people captured with several standard cameras. Our system features a novel technique for generating view-independent texture atlases computed from the original images, and two proposals for improving the quality of the facial region of the 3D mesh: a purely passive one implying no additional cost, and another based on active techniques such as structured light projection.

We propose a novel technique for modeling and rendering a 3D point cloud obtained from a set of photographs of a real 3D scene as a set of textured elliptical splats. We first obtain the base splat model by calculating, for each point of the cloud, an ellipse approximating locally the underlying surface. We then refine the base model by removing redundant splats to minimize overlaps, and merging splats covering flat regions of the point cloud into larger ellipses. We later apply a multi-texturing process to generate a single texture atlas from the set of photographs, by blending information from multiple cameras for every splat. Finally, we render this multi-textured, splat-based 3D model with an efficient implementation of OpenGL ES 2.0 vertex and fragment shaders which guarantees its fluid display on handheld devices.

We propose a hybrid 3D modeling and rendering approach called SPLASH to combine the modeling flexibility and robustness of SPLAts together with the rendering simplicity and maturity of meSHes. Together with this novel SPLASH concept, we also propose a system turning a 3D point cloud, obtained for example through an SfM (Structure from Motion) approach, into a multi-textured hybrid 3D model whose shape is described by a triangle mesh plus a collection of elliptical splats.

There is an increasing need of easy and affordable technologies to automatically generate virtual 3D models from their real counterparts. In particular, 3D human reconstruction has driven the creation of many clever techniques, most of them based on the visual hull (VH) concept. Such techniques do not require expensive hardware; however, they tend to yield 3D humanoids with realistic bodies but mediocre faces, since VH cannot handle concavities. On the other hand, structured light projectors allow to capture very accurate depth data, and thus to reconstruct realistic faces, but they are too expensive to use several of them. We have developed a technique to merge a VH-based 3D mesh of a reconstructed humanoid and the depth data of its face, captured by a single structured light projector. By combining the advantages of both systems in a simple setting, we are able to reconstruct realistic 3D human models with believable faces.

We introduce an innovative, semi-automatic method to transform low resolution facial meshes into high definition ones, based on the tailoring of a generic, neutral human head model, designed by an artist, to fit the facial features of a specific person. To determine these facial features we need to select a set of "control points" (corners of eyes, lips, etc.) in at least two photographs of the subject's face. The neutral head mesh is then automatically reshaped according to the relation between the control points in the original subject's mesh through a set of transformation pyramids. The last step consists in merging both meshes and filling the gaps that appear in the previous process. This algorithm avoids the use of expensive and complicated technologies to obtain depth maps, which also need to be meshed later.

We introduce a simple and innovative method to compare any two texture maps, regardless of their sizes, aspect ratios, or even masks, as long as they are both meant to be mapped onto the same 3D mesh. Our system is based on a zero-distortion 3D mesh unwrapping technique which compares two new adapted texture atlases with the same mask but different texel colors, and whose every texel covers the same area in 3D. Once these adapted atlases are created, we measure their difference with ITEM-RMSE, a slightly modified version of the standard RMSE defined for images. ITEM-RMSE is more meaningful and reliable than RMSE because it only takes into account the texels inside the mask, since they are the only ones that will actually be used during rendering. Our method is not only very useful to compare the space efficiency of different texture atlas generation algorithms, but also to quantify texture loss in compression schemes for multi-resolution textured 3D meshes.