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We address shape grammar parsing for facade segmen-tation using Reinforcement Learning (RL). Shape parsing entails simultaneously optimizing the geometry and the topology (e.g. number of floors) of the facade, so as to optimize the fit of the predicted shape with the responses of pixel-level 'terminal detectors'. We formulate this problem in terms of a(More)
In this paper we propose a novel approach to the perceptual interpretation of building facades that combines shape grammars, supervised classification and random walks. Procedural modeling is used to model the geometric and the photometric variation of buildings. This is fused with visual classification techniques (randomized forests) that provide a crude(More)
In this paper we introduce a novel approach to single view reconstruction using shape grammars. Our approach consists in modeling architectural styles using a set of basic shapes and a set of parametric rules, corresponding to increasing levels of detail. This approach is able to model elaborate and varying architectural styles, using a tree representation(More)
In this paper we tackle the problem of 3D modeling for urban environment using a modular, flexible and powerful approach driven from procedural generation. To this end, typologies of architectures are modeled through shape grammars that consist of a set of derivation rules and a set of shape/dictionary elements. Appearance (from statistical point of view(More)
In this paper, we use shape grammars (SGs) for facade parsing, which amounts to segmenting 2D building facades into balconies, walls, windows, and doors in an architecturally meaningful manner. The main thrust of our work is the introduction of reinforcement learning (RL) techniques to deal with the computational complexity of the problem. RL provides us(More)
In this paper we address multi-view reconstruction of urban environments using 3D shape grammars. Our formulation expresses the solution to the problem as a shape grammar parse tree where both the tree and the corresponding derivation parameters are unknown. Besides the grammar constraint, the solution is guided by an image support that is twofold. First,(More)
In this paper, we propose a novel one-shot optimization approach to simultaneously determine both the optimal 3D landmark model and the corresponding 2D projections without explicit estimation of the camera viewpoint, which is also able to deal with misdetections as well as partial occlusions. To this end, a 3D shape manifold is built upon fourth-order(More)
  • Sophie Vaux, Alexis Criscuolo, Marie Desnos-Ollivier, Laure Diancourt, Chloé Tarnaud, Matthias Vandenbogaert +122 others
  • 2014
UNLABELLED Rapidly fatal cases of invasive fungal infections due to a fungus later identified as Saprochaete clavata were reported in France in May 2012. The objectives of this study were to determine the clonal relatedness of the isolates and to investigate possible sources of contamination. A nationwide alert was launched to collect cases. Molecular(More)
Low-dose CT-like imaging systems offer numerous perspectives in terms of clinical application, in particular for osteoarticular diseases. In this paper, we address the challenging problem of 3D femur modeling and estimation from bi-planar views. Our contributions are threefold. First, we propose a non-uniform hierarchical decomposition of the shape prior of(More)