Sketching-out virtual humans: A smart interface for human modelling and animation

In this paper, we present a fast and intuitive interface for sketching out 3D virtual humans and animation. The user draws stick figure key frames first and chooses one for “fleshing-out” with freehand body contours. The system automatically constructs a plausible 3D skin surface from the rendered figure, and maps it onto the posed stick figures to produce the 3D character animation. A “creative model-based method” is developed, which performs a human perception process to generate 3D human bodies of various body sizes, shapes and fat distributions. In this approach, an anatomical 3D generic model has been created with three distinct layers: skeleton, fat tissue, and skin. It can be transformed sequentially through rigid morphing, fatness morphing, and surface fitting to match the original 2D sketch. An auto-beautification function is also offered to regularise the 3D asymmetrical bodies from users’ imperfect figure sketches. Our current system delivers character animation in various forms, including articulated figure animation, 3D mesh model animation, 2D contour figure animation, and even 2D NPR animation with personalised drawing styles. The system has been formally tested by various users on Tablet PC. After minimal training, even a beginner can create vivid virtual humans and animate them within minutes

Posing 3D Models from Drawing

Inferring the 3D pose of a character from a drawing is a complex and under-constrained problem. Solving it may help automate various parts of an animation production pipeline such as pre-visualisation. In this paper, a novel way of inferring the 3D pose from a monocular 2D sketch is proposed. The proposed method does not make any external assumptions about the model, allowing it to be used on different types of characters. The inference of the 3D pose is formulated as an optimisation problem and a parallel variation of the Particle Swarm Optimisation algorithm called PARAC-LOAPSO is utilised for searching the minimum. Testing in isolation as well as part of a larger scene, the presented method is evaluated by posing a lamp, a horse and a human character. The results show that this method is robust, highly scalable and is able to be extended to various types of models

Robust Blockwise Random Pivoting: Fast and Accurate Adaptive Interpolative Decomposition

The interpolative decomposition (ID) aims to construct a low-rank approximation formed by a basis consisting of row/column skeletons in the original matrix and a corresponding interpolation matrix. This work explores fast and accurate ID algorithms from five essential perspectives for empirical performance: (a) skeleton complexity that measures the minimum possible ID rank for a given low-rank approximation error, (b) asymptotic complexity in FLOPs, (c) parallelizability of the computational bottleneck as matrix-matrix multiplications, (d) error-revealing property that enables automatic rank detection for given error tolerances without prior knowledge of target ranks, (e) ID-revealing property that ensures efficient construction of the optimal interpolation matrix after selecting the skeletons. While a broad spectrum of algorithms have been developed to optimize parts of the aforementioned perspectives, practical ID algorithms proficient in all perspectives remain absent. To fill in the gap, we introduce robust blockwise random pivoting (RBRP) that is parallelizable, error-revealing, and exact-ID-revealing, with comparable skeleton and asymptotic complexities to the best existing ID algorithms in practice. Through extensive numerical experiments on various synthetic and natural datasets, we empirically demonstrate the appealing performance of RBRP from the five perspectives above, as well as the robustness of RBRP to adversarial inputs

Making masks for Maui: Keeping the macro task in mind

New Zealand primary school children in technology lessons often design and create an artifact in response to a scenario that relates to their interests and experiences. Usually the task is undertaken over several days. In this paper we draw on data generated within the INSiTE study, a three-year study exploring the nature of effective student-teacher interactions around science and technology ideas. The teacher in this paper planned for her children to create a mask for their forthcoming school production: 'How Maui found the secret of fire'. As the children worked on the macro task, that of designing and making a mask, meso and micro tasks emerged. The teacher assisted the children to identity and resolve these, hearing in mind that the ultimate aim was their successful participation in the school production. When teachers assist children to maintain a focus on the overall or macro task goals their artifact fulfils the specifications of the scenario and children's technology understandings and skills are fostered

Matisse : Painting 2D regions for Modeling Free-Form Shapes

International audienceThis paper presents "Matisse", an interactive modeling system aimed at providing the public with a very easy way to design free-form 3D shapes. The user progressively creates a model by painting 2D regions of arbitrary topology while freely changing the view-point and zoom factor. Each region is converted into a 3D shape, using a variant of implicit modeling that fits convolution surfaces to regions with no need of any optimization step. We use intuitive, automatic ways of inferring the thickness and position in depth of each implicit primitive, enabling the user to concentrate only on shape design. When he or she paints partly on top of an existing primitive, the shapes are blended in a local region around the intersection, avoiding some of the well known unwanted blending artifacts of implicit surfaces. The locality of the blend depends on the size of smallest feature, enabling the user to enhance large, smooth primitives with smaller details without blurring the latter away. As the results show, our system enables any unprepared user to create 3D geometry in a very intuitive way