We tackle the digital divide issue from the user experience point of view. Our study aim at obtaining information on the impact of UI/UX design choices on the participants’ achievement strategies. In that prospect, we asked voluntary participants receiving social benefits at a social action center to perform typical account management tasks on two French administration websites. Then we analyzed their visual exploration strategies. The results of this preliminary study suggest that highly symbolic pictographic representations are ignored by users in a situation of digital precariousness. They spend a large amount of time looking through the textual content to find indications, submenus or links to navigate rather than exploiting the shorthand access provided through the abstract icon system. These ergonomic choices constitute an additional barrier to the use of these technologies by fragile users.

Purpose Locating the internal structures of an organ is a critical aspect of many surgical procedures. Minimally invasive surgery, associated with augmented reality techniques, offers the potential to visualize inner structures, allowing for improved analysis, depth perception or for supporting planning and decision systems. Methods Most of the current methods dealing with rigid or non-rigid augmented reality make the assumption that the topology of the organ is not modified. As surgery relies essentially on cutting and dissection of anatomical structures, such methods are limited to the early stages of the surgery. We solve this shortcoming with the introduction of a method for physics-based elastic registration using a single view from a monocular camera. Singularities caused by topological changes are detected and propagated to the preoperative model. This significantly improves the coherence between the actual laparoscopic view and the model and provides added value in terms of navigation and decision-making, e.g., by overlaying the internal structures of an organ on the laparoscopic view. Results Our real-time augmentation method is assessed on several scenarios, using synthetic objects and real organs. In all cases, the impact of our approach is demonstrated, both qualitatively and quantitatively ( http://www.open-cas.org/?q=PaulusIJCARS16 ). Conclusion The presented approach tackles the challenge of localizing internal structures throughout a complete surgical procedure, even after surgical cuts. This information is crucial for surgeons to improve the outcome for their surgical procedure and avoid complications.

We present CPH Compact Primal Hierarchy: a compact representation of the hierarchical connectivity of surface and volume manifold meshes generated through primal subdivision refinements. CPH is consistently defined in several dimensions and supports multiple kinds of tessellations and refinements, whether regular or adaptive. The basic idea is to store only the finest mesh, encoded in a classical monoresolution structure that is enriched with a minimal set of labels. These labels allow traversal of any intermediate level of the mesh concurrently without having to extract it in an additional structure. Our structure allows attributes to be stored on the cells not only on the finest level, but also on any intermediate level. We study the trade-off between the memory cost of this compact representation and the time complexity of mesh traversals at any resolution level.

The visualization of internal structures of organs in minimally invasive surgery is an important avenue for improving the perception of the surgeon, or for supporting planning and decision systems. However, current methods dealing with non-rigid augmented reality only provide augmentation when the topology of the organ is not modified. In this paper we solve this shortcoming by introducing a method for physics-based non-rigid augmented reality. Singularities caused by topological changes are detected and propagated to the pre-operative model. This significantly improves the coherence between the actual laparascopic view and the model, and provides added value in terms of navigation and decision making. Our real time augmentation algorithm is assessed on a video showing the cut of a porcine liver's lobe in minimal invasive surgery.

Virtual cutting of deformable objects is at the core of many applications in interactive simulation and especially in computational medicine. The ability to simulate surgical cuts, dissection, soft tissue tearing or micro-fractures is essential for augmenting the capabilities of existing or future simulation systems. To support such features, we combine a new remeshing algorithm with a fast finite element approach. The proposed method is generic enough to support a large variety of applications. We show the benefits of our approach evaluating the impact of cuts on the number of nodes and the numerical quality of the mesh. These points are crucial to ensure accurate and stable real-time simulations.

Current methods dealing with non-rigid augmented reality only provide an augmented view when the topology of the tracked object is not modified, which is an important limitation. In this paper we solve this shortcoming by introducing a method for physics-based non-rigid augmented reality. Singularities caused by topological changes are detected by analyzing the displacement field of the underlying deformable model. These topological changes are then applied to the physics-based model to approximate the real cut. All these steps, from deformation to cutting simulation, are performed in real-time. This significantly improves the coherence between the actual view and the model, and provides added value.

To produce impressive virtual worlds, real-time crowd simulations require large and detailed scenes populated by agents with complex shapes and geometry. For efficiency reasons, these agents are usually approximated by point-like representations to optimize the performances of collision avoidance and interactions between agents. This paper addresses the issue of handling deformable polygonal agents with arbitrary shapes in real time crowd simulations. The proposed multiresolution framework supports environments with arbitrary topologies and provides tools for efficient proximity queries. Copyright © 2014 John Wiley & Sons, Ltd.

We present a new model for the representation of n-dimensional multiresolution meshes. It provides a robust topological representation of arbitrary meshes that are combined in closely interlinked levels of resolution. The proposed combinatorial model is formalized through the mathematical model of combinatorial maps allowing us to give a general formulation, in any dimensions, of the topological subdivision process that is a key issue to robustly and soundly define mesh hierarchies. It fully supports multiresolution edition what allows the implementation of most mesh processing algorithms - like filtering or compression - for n-dimensional meshes with arbitrary topologies.We illustrate this model, in dimension 3, with an new truly multiresolution representation of subdivision volumes. It allows us to extend classical subdivision schemes to arbitrary polyhedrons and to handle adaptive subdivision with an elegant solution to compliance issues. We propose an implementation of this model as an effective and relatively inexpensive data structure. (C) 2013 Elsevier Inc. All rights reserved.

Many data structures are available for the representation and manipulation of meshes. In the context of algorithms that need to traverse local neighborhoods, topological structures are of particular interest. Many such existing structures are specialized for the representation of objects of a given dimension like surface or volume meshes. Many of them find their roots in combinatorial maps, a mathematical model for the representation of the topology of the subdivision of objects, which is consistently defined in any dimension.We present a practical implementation of combinatorial maps that competes with modern state-of-the-art data structures in terms of efficiency, memory footprint and usability. Among other benefits, developers can use a single consistent library to manipulate objects of various dimensions.

ABSTRACTRealistic simulation of crowds is an important issue for the production of virtual worlds for games, entertainment or architectural and urban planning. Difficult issues need to be addressed such as collision avoidance and the handling of dynamic environments. In this paper, we present a unified structure for the simulation of crowds in complex urban environments. We propose a topological multiresolution model supporting different levels of details, allowing efficient proximity querying and compatible with real‐time rendering and hierarchical path planning. A fine exploitation of the multiscale aspect of the underlying model allows to achieve the same efficiency as the fastest existing methods. The generality of the approach allows the simulation to be executed on any two manifold, and the unified approach eases the handling of dynamic environments. Copyright © 2012 John Wiley & Sons, Ltd.

La representation multiresolution d’objets modelises est devenue monnaie courante ces dernieres annees en informatique graphique. On peut notamment citer les surfaces de subdivision regulierement abordees en modelisation geometrique. Elles possedent des structures de donnees tel la version multiresolution des demi-aretes (et des 2-cartes combinatoires) ou encore le quadtree pour manipuler differents niveaux de resolution. A l’inverse, cette question de la representation multiresolution et adaptative des volumes de subdivision reste ouverte pour des maillages polyedriques. Pourtant, le processus de subdivision peine par la quantite de donnees, geometriques et topologiques produite. Dans ce travail, nous proposons une nouvelle structure de donnees pour la representation et la manipulation efficace de solides de subdivision multiresolution adaptative. Notre modele topologique permet une navigation instantanee et efficace a tout niveau de resolution du maillage. Sa representation est formalisee dans le cadre des cartes combinatoires pour nous permettre de donner une formulation tres generale des changements topologiques.

We present in this paper a new approach to detect and precisely report the collisions and contacts betwe en deformable moving bodies and their environment. The moving bodies are sampled as meshes whose vertices are followed up in a convex subdivision of the surrounding space. Particlesare continuously spanned along the edges to detect collisions w ith cells of this subdivision. We report experimentations with shape matching based physical simulations and discuss performance of our method. We compare our approach with hierarchical ones.

Reconstructing tubular structures with high-order branching is a difficult task to perform automatically. Medical applications in particular demand accurate models of such objects that fulfill specific topological and geometric criteria. Indeed, the reconstructed object should be a 2-manifold surface with compact, adaptive geometry. We present a generic algorithm for automatically reconstructing n-furcated tubular surfaces. Our approach relies on a strong underlying topological structure and a novel n-furcation reconstruction algorithm using convex entities.

We present in this paper a simulation framework that allows a precise and efficient handling of collisions and contacts between deformable moving bodies and their environment. The moving bodies are sampled as meshes whose vertices are followed in a convex subdivision of the surrounding space. Particles are continuously spanned along the edges to detect collisions with cells of this subdivision. Our method supports dynamic subdivision of the moving bodies and contact areas. It allows us to correctly handle geometric and topological changes in the environment, like cuts, tears or breaks and, more generally, additions or removals of material. We report experimental results obtained with mass spring and shape matching based physical simulations and discuss the performance of our method. We compare our approach with classical ones based on hierarchical data structures.

Many representation schemes have been proposed to deal with non-manifold and mixed dimensionalities objects. A majority of those models are based on incidence graphs and although they provide efficient ways to query topological adjacencies, they suffer two major drawbacks: redundancy in the storage of topological entities and relationships, and the lack of a uniform representation of those entities that leads to the development of large sets of intricate topological operators. As regards to manifold meshes - and specifically triangular ones - compact and efficient models are known for twenty years. Ordered topological models like combinatorial maps or half edges based data structures are widely studied and used. We propose a new representation scheme - the extended maps or X-maps - that enhances those models to deal with non-manifold objects and mixed dimensionalities. We exhibit properties that allows an adaptive implementation of the cells and thus ensures that X-maps scale well in case of large surface areas or manifold pieces. We show that the storage requirements for X-maps is strongly reduced compared to the radial edge and similar structures and also present optimizations in case of triangular or tetrahedral non-manifold meshes.

Collision detection in geometrically complex scenes is crucial in physical simulations and real time applications. Works based on spatial hierarchical structures have been proposed for years. If correct performances are obtained for static scenes, these approaches show some limitations when the complexity of the scene increases and particularly in case of deformable meshes. The main drawback is the time needed to update the spatial structures - often trees - when global deformations or topological changes occur in the scene. We propose a method to detect collisions in complex and deformable environments with constant time amortized complexity for small displacements. Our method is based on a convex decomposition of the environment coupled with a forecast mechanism exploiting temporal coherence. We use the topological adjacencies and incidence relationships to reduce the number of geometrical tests. Deformations of the scenes are handled with no cost as far as no topological changes occur. Topological transformations, like cuts and sewings, are handled locally, exploiting the spatial coherence and do not imply global updates. We illustrate our method in two experimental frameworks: a particles flow simulation and a meshless animation system both lying in a deformable mesh. We compare our work with classical optimization based on bounding volumes hierarchies to validate its efficiency on large scenes.

La detection de collisions entre un mobile et son environnement est cruciale dans le contexte des applications de simulation physique. Beaucoup de methodes ont ete proposees pour accelerer cette detection dans une scene complexe en vue de respecter la contrainte de l'interactivite. Cependant, lorsque l'environnement devient deformable, les optimisations de ces structures basees sur l'utilisation de structures hierarchiques trouvent leurs limites au niveau du temps de mise a jour.Nous proposons dans cet article une methode basee sur une subdivision volumique de l'environnement couplee a un mecanisme de prediction. L'environnement est subdivise en un ensemble de cellules convexes enrichi par une structure topologique forte permettant des requetes de voisinages optimales. Ce systeme de prediction utilise la coherence temporelle et les proprietes des cellules pour optimiser le nombre de tests d'intersection a effectuer a chaque pas de temps.Nous illustrons notre methode avec l'animation de flots de particules dans des maillages deformables.

We address in this paper the problem of the data structures used for the representation and the manipulation of multiresolution subdivision surfaces. The classically used data structures are based on quadtrees, straightforwardly derived from the nested hierarchy of faces generated by the subdivision schemes. Nevertheless, these structures have some drawbacks: specificity to the kind of mesh (triangle or quad); the time complexity of neighborhood queries is not optimal; topological cracks are created in the mesh in the adaptive subdivision case.We present in this paper a new topological model for encoding multiresolution subdivision surfaces. This model is an extension to the well-known half-edge data structure. It allows instant and efficient navigation at any resolution level of the mesh. Its generality allows the support of many subdivision schemes including primal and dual schemes. Moreover, subdividing the mesh adaptively does not create topological cracks in the mesh. The extension proposed here is formalized in the combinatorial maps framework. This allows us to give a very general formulation of our extension.