Cataloged from PDF version of article.We simulate virtual crowds in emergency situations caused by an incident, such as a fire, an explosion, or a terrorist attack. We use a continuum dynamics-based approach to simulate the escaping crowd, which produces more efficient simulations than the agent-based approaches. Only the close proximity of the incident region, which includes the crowd affected by the incident, is simulated. We use a model-based rendering approach where a polygonal mesh is rendered for each agent according to the agent's skeletal motion. To speed up the animation and visualization, we employ an offline occlusion culling technique. We animate and render a pedestrian model only if it is visible according to the static visibility information computed. In the pre-processing stage, the navigable area is decomposed into a grid of cells and the from-region visibility of these cells is computed with the help of hardware occlusion queries. (C) 2009 Elsevier Ltd. All rights reserved
Abstract. We propose adaptive grids, an image-based approach for constructing navigation meshes, which are used for path planning. A cellular navigation mesh, called an adaptive grid, is constructed from a top-view range image of a three-dimensional urban model. A navigation graph can then be extracted from this adaptive grid for path planning. We compare our approach with two popular navigation mesh-generation approaches and obtain promising results in terms of path accuracy and memory cost.
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