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.

Abstract 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.

ABSTRACT 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.

ABSTRACT Realistic 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.

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.

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.

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.