71 research outputs found

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

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    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

    Embedded Implicit Stand-ins for Animated Meshes: a Case of Hybrid Modelling

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    In this paper we address shape modelling problems, encountered in computer animation and computer games development that are difficult to solve just using polygonal meshes. Our approach is based on a hybrid modelling concept that combines polygonal meshes with implicit surfaces. A hybrid model consists of an animated polygonal mesh and an approximation of this mesh by a convolution surface stand-in that is embedded within it or is attached to it. The motions of both objects are synchronised using a rigging skeleton. This approach is used to model the interaction between an animated mesh object and a viscoelastic substance, normally modelled in implicit form. The adhesive behaviour of the viscous object is modelled using geometric blending operations on the corresponding implicit surfaces. Another application of this approach is the creation of metamorphosing implicit surface parts that are attached to an animated mesh. A prototype implementation of the proposed approach and several examples of modelling and animation with near real-time preview times are presented

    Shape Modeling by Sketching using Convolution Surfaces

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    International audienceThis paper proposes a user-friendly modeling system that interactively generates 3D organic-like shapes from user drawn sketches. A skeleton, in the form of a graph of branching polylines and polygons, is first extracted from the user's sketch. The 3D shape is then defined as a convolution surface generated by this skeleton. The skeleton's resolution is adapted according to the level of detail selected by the user. The subsequent 2D strokes are used to infer new object parts, which are combined with the existing shape using CSG operators. We propose an algorithm for computing a skeleton defined as a connected graph of polylines and polygons. To combine the primitives we propose precise CSG operators for a convolution surfaces blending hierarchy. Our new formulation has the advantage of requiring no optimization step for fitting the 3D shape to the 2D contours. This yields interactive performances and avoids any non-desired oscillation of the reconstructed surface. As our results show, our system allows nonexpert users to generate a wide variety of free form shapes with an easy to use sketch-based interface

    High-quality tree structures modelling using local convolution surface approximation

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    In this paper, we propose a local convolution surface approximation approach for quickly modelling tree structures with pleasing visual effect. Using our proposed local convolution surface approximation, we present a tree modelling scheme to create the structure of a tree with a single high-quality quad-only mesh. Through combining the strengths of the convolution surfaces, subdivision surfaces and GPU, our tree modelling approach achieves high efficiency and good mesh quality. With our method, we first extract the line skeletons of given tree models by contracting the meshes with the Laplace operator. Then we approximate the original tree mesh with a convolution surface based on the extracted skeletons. Next, we tessellate the tree trunks represented by convolution surfaces into quad-only subdivision surfaces with good edge flow along the skeletal directions. We implement the most time-consuming subdivision and convolution approximation on the GPU with CUDA, and demonstrate applications of our proposed approach in branch editing and tree composition

    3D free-form modeling with variational surfaces

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    We describe a free-form stroke-based modeling system where objects are primarily represented by means of variational surfaces. Although similar systems have been described in recent years, our approach achieves both a good performance and reduced surface leak problems by employing a coarse mesh as support for constraint points. The prototype implements an adequate set of modeling operations, “undo” and “redo” facilities and a clean interface capable of resolving ambiguities by means of suggestion thumbnails

    Playing with Puffball: Simple Scale-Invariant Inflation for Use in Vision and Graphics

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    We describe how inflation, the act of mapping a 2D silhouette to a 3D region, can be applied in two disparate problems to offer insight and improvement: silhouette part segmentation and image-based material transfer. To demonstrate this, we introduce Puffball, a novel inflation technique, which achieves similar results to existing inflation approaches -- including smoothness, robustness, and scale and shift-invariance -- through an exceedingly simple and accessible formulation. The part segmentation algorithm avoids many of the pitfalls of previous approaches by finding part boundaries on a canonical 3-D shape rather than in the contour of the 2-D shape; the algorithm gives reliable and intuitive boundaries, even in cases where traditional approaches based on the 2D Minima Rule are misled. To demonstrate its effectiveness, we present data in which subjects prefer Puffball's segmentations to more traditional Minima Rule-based segmentations across several categories of silhouettes. The texture transfer algorithm utilizes Puffball's estimated shape information to produce visually pleasing and realistically synthesized surface textures with no explicit knowledge of either underlying shape.National Eye Institute (Special Training Grant

    Nested Explorative Maps: A new 3D canvas for conceptual design in architecture

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    International audienceIn this digital age, architects still need to alternate between paper sketches and 3D modeling software for their designs. Indeed, while 3D models enable to explore different views, creating them at very early stages might reduce creativity since they do not allow to superpose several tentative designs nor to refine them progressively, as sketches do. To enable exploratory design in 3D, we introduce Nested Explorative Maps, a new system dedicated to interactive design in architecture. Our model enables coarse to fine sketching of nested architectural structures, enabling to progressively sketch a 3D building from floor plan to interior design, thanks to a series of nested maps able to spread in 3D. Each map allows the visual representation of uncertainty as well as the interactive exploration of the alternative, tentative options. We validate the model through a user study conducted with professional architects, enabling us to highlight the potential of Nested Explorative Maps for conceptual design in architecture.En cette Ăšre du numĂ©rique, les architectes doivent encore alterner entre le croquis papier et logiciels de modĂ©lisation 3D afin de rĂ©aliser leurs conceptions. En effet, les modĂšles 3D permettent d’explorer diffĂ©rentes vues mais leur crĂ©ation Ă  un stade trĂšs prĂ©coce peut impliquer une perte de la crĂ©ativitĂ© car ils ne permettent pas de superposer plusieurs plans provisoires ni de les affiner progressivement, comme le font les esquisses. Pour permettre la conception exploratoire dans l'espace 3D, nous prĂ©sentons Nested Explorative Maps, un nouveau systĂšme dĂ©diĂ© Ă  la conception interactive en architecture. Notre modĂšle permet de dessiner du grossier aux dĂ©tails des structures architecturales imbriquĂ©es, afin de dessiner progressivement un bĂątiment en 3D, du plan Ă  la dĂ©coration intĂ©rieure, grĂące Ă  une sĂ©rie de cartes imbriquĂ©es capables de se rĂ©pandre en 3D. Chaque carte permet de reprĂ©senter visuellement l’incertitude et d’explorer de maniĂšre interactive les diffĂ©rentes options possibles. Une Ă©tude utilisateur rĂ©alisĂ©e auprĂšs d'architectes professionnels nous a permis de valider notre modĂšle et de mettre en Ă©vidence le potentiel des cartes exploratoires imbriquĂ©es pour la conception conceptuelle en architecture

    Object detection and activity recognition in digital image and video libraries

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    This thesis is a comprehensive study of object-based image and video retrieval, specifically for car and human detection and activity recognition purposes. The thesis focuses on the problem of connecting low level features to high level semantics by developing relational object and activity presentations. With the rapid growth of multimedia information in forms of digital image and video libraries, there is an increasing need for intelligent database management tools. The traditional text based query systems based on manual annotation process are impractical for today\u27s large libraries requiring an efficient information retrieval system. For this purpose, a hierarchical information retrieval system is proposed where shape, color and motion characteristics of objects of interest are captured in compressed and uncompressed domains. The proposed retrieval method provides object detection and activity recognition at different resolution levels from low complexity to low false rates. The thesis first examines extraction of low level features from images and videos using intensity, color and motion of pixels and blocks. Local consistency based on these features and geometrical characteristics of the regions is used to group object parts. The problem of managing the segmentation process is solved by a new approach that uses object based knowledge in order to group the regions according to a global consistency. A new model-based segmentation algorithm is introduced that uses a feedback from relational representation of the object. The selected unary and binary attributes are further extended for application specific algorithms. Object detection is achieved by matching the relational graphs of objects with the reference model. The major advantages of the algorithm can be summarized as improving the object extraction by reducing the dependence on the low level segmentation process and combining the boundary and region properties. The thesis then addresses the problem of object detection and activity recognition in compressed domain in order to reduce computational complexity. New algorithms for object detection and activity recognition in JPEG images and MPEG videos are developed. It is shown that significant information can be obtained from the compressed domain in order to connect to high level semantics. Since our aim is to retrieve information from images and videos compressed using standard algorithms such as JPEG and MPEG, our approach differentiates from previous compressed domain object detection techniques where the compression algorithms are governed by characteristics of object of interest to be retrieved. An algorithm is developed using the principal component analysis of MPEG motion vectors to detect the human activities; namely, walking, running, and kicking. Object detection in JPEG compressed still images and MPEG I frames is achieved by using DC-DCT coefficients of the luminance and chrominance values in the graph based object detection algorithm. The thesis finally addresses the problem of object detection in lower resolution and monochrome images. Specifically, it is demonstrated that the structural information of human silhouettes can be captured from AC-DCT coefficients

    SCALe-invariant Integral Surfaces

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    International audienceExtraction of skeletons from solid shapes has attracted quite a lot of attention, but less attention was paid so far to the reverse operation: generating smooth surfaces from skeletons and local radius information. Convolution surfaces, i.e. implicit surfaces generated by integrating a smoothing kernel along a skeleton, were developed to do so. However, they failed to reconstruct prescribed radii and were unable to model large shapes with fine details. This work introduces SCALe-invariant Integral Surfaces (SCALIS), a new paradigm for implicit modeling from skeleton graphs. Similarly to convolution surfaces, our new surfaces still smoothly blend when field contributions from new skeleton parts are added. However, in contrast with convolution surfaces, blending properties are scale invariant. This brings three major benefits: the radius of the surface around a skeleton can be explicitly controlled, shapes generated in blending regions are self-similar regardless of the scale of the model, and thin shape components are not excessively smoothed out when blended into larger ones

    Convolution Surfaces based on Polygons for Infinite and Compact Support Kernels

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    International audienceWe provide formulae to create 3D smooth shapes fleshing out a skeleton made of line segments and planar polygons. The boundary of the shape is a level set of the convolution function obtained by integration along the skeleton. The convolution function for a complex skeleton is thus the sum of the convolution functions for the basic elements of the skeleton. Providing formulae for the convolutionof a polygon is the main contribution of the present paper. We improve on previous results in several ways. First we do not require the prior triangulation of the polygon. Then, we obtain formulae for families of kernels, either with infinite or compact supports. Last, but not least, in the case of compact support kernels, the geometric computations needed are restricted to intersections of spheres with line segments
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