In this paper we present an intuitive tool suitable for 2D artists using touch-enabled pen tablets. An artist-oriented tool should be easy-to-use, real-time, versatile, and locally refinable. Our approach uses an interactive system for 3D character posing from 2D strokes. We employ a closed-form solution for the 2D strokes to 3D skeleton registration problem. We first construct an intermediate 2D stroke representation by extracting local features using meaningful heuristics. Then, we match 2D stroke segments to 3D bones. Finally, 3D bones are carefully realigned with the matched 2D stroke segments while enforcing important constraints such as bone rigidity and depth. Our technique is real-time and has a linear time complexity. It is versatile, as it works with any type of 2D stroke and 3D skeleton input. Finally, thanks to its coarse-to-fine design, it allows users to perform local refinements and thus keep full control over the final results. We demonstrate that our system is suitable for 2D artists using touch-enabled pen tablets by posing 3D characters with heterogeneous topologies (bipeds, quadrupeds, hands) in real-time.

In this article, we present a parallel prioritized Jacobian-based inverse kinematics algorithm for multithreaded architectures. We solve damped least squares inverse kinematics using a parallel line search by identifying and sampling critical input parameters. Parallel competing execution paths are spawned for each parameter in order to select the optimum that minimizes the error criteria. Our algorithm is highly scalable and can handle complex articulated bodies at interactive frame rates. We show results on complex skeletons consisting of more than 600 degrees of freedom while being controlled using multiple end effectors. We implement the algorithm both on multicore and GPU architectures and demonstrate how the GPU can further exploit fine-grain parallelism not directly available on a multicore processor. Our implementations are 10 to 150 times faster compared to a state-of-the-art serial implementation while providing higher accuracy. We also demonstrate the scalability of the algorithm over multiple scenarios and explore the GPU implementation in detail.

Displays remain flat and passive amidst the many changes in their fundamental technologies. One natural step ahead is to create displays that merge seamlessly in shape and appearance with one’s natural surroundings. In this paper, we present a system to design, render to, and build view-dependent multiplanar displays of arbitrary piecewise-planar shapes, built using polygonal facets. Our system provides high quality, interactive rendering of 3D environments to a head-tracked viewer on arbitrary multiplanar displays. We develop a novel rendering scheme that produces exact image and depth map at each facet, producing artifact-free images on and across facet boundaries. The system scales to a large number of display facets by rendering all facets in a single pass of rasterization. This is achieved using a parallel, perframe, view-dependent binning and prewarping of scene triangles. The display is driven using one or more target quilt images into which facet pixels are packed. Our method places no constraints on the scene or the display and allows for fully dynamic scenes to be rendered interactively at high resolutions. The steps of our system are implemented efficiently on commodity GPUs. We present a few prototype displays to establish the scalability of our system on different display shapes, form factors, and complexity: from a cube made out of LCD panels to spherical/cylindrical projected setups to arbitrary complex shapes in simulation. Performance of our system is demonstrated for both rendering quality and speed, for increasing scene and display facet sizes. A subjective user study is also presented to evaluate the user experience using a walk-around display compared to a flat panel for a game-like setting.

Cluster-based tiled display walls can provide cost-effective and scalable displays with high resolution and a large display area. The software to drive them needs to scale too if arbitrarily large displays are to be built. Chromium is a popular software API used to construct such displays. Chromium transparently renders any OpenGL application to a tiled display by partitioning and sending individual OpenGL primitives to each client per frame. Visualization applications often deal with massive geometric data with millions of primitives. Transmitting them every frame results in huge network requirements that adversely affect the scalability of the system. In this paper, we present Garuda, a client-server-based display wall framework that uses off-the-shelf hardware and a standard network. Garuda is scalable to large tile configurations and massive environments. It can transparently render any application built using the Open Scene Graph (OSG) API to a tiled display without any modification by the user. The Garuda server uses an object-based scene structure represented using a scene graph. The server determines the objects visible to each display tile using a novel adaptive algorithm that culls the scene graph to a hierarchy of frustums. Required parts of the scene graph are transmitted to the clients, which cache them to exploit the interframe redundancy. A multicast-based protocol is used to transmit the geometry to exploit the spatial redundancy present in tiled display systems. A geometry push philosophy from the server helps keep the clients in sync with one another. Neither the server nor a client needs to render the entire scene, making the system suitable for interactive rendering of massive models. Transparent rendering is achieved by intercepting the cull, draw, and swap functions of OSG and replacing them with our own. We demonstrate the performance and scalability of the Garuda system for different configurations of display wall. We also show that the server and network loads grow sublinearly with the increase in the number of tiles, which makes our scheme suitable to construct very large displays.