Simulation, Animation and Rendering of Crowds in Real-Time

Abstract

Nowadays crowd simulation is becoming more important in computer applications such as building evacuation planning, training, videogames, etc., presenting hundreds or thousands of agents navigating in virtual environments. Some of these applications need to run in real time in order to offer complete interaction with the user. Simulated crowds should seem natural and give a good looking impression to the user. The goal should be to produce both the best motion and animation, while minimizing the awkwardness of movements and eliminating or hiding visual artifacts. Achieving simulation, animation and rendering of crowds in real-time becomes thus a major challenge. Although each of these areas has been studied individually and improvements have been made in the literature, its integration in one real-time system is not straight forward. In the process of integrating animation, simulation and rendering of real time crowds, we need to assume some trade-offs between accuracy and quality of results. The main goal of this thesis is to work on those three aspects of a real-time crowd visualization (simulation, animation and rendering) seeking for possible speed-ups and optimizations allowing us to further increase the number of agents in the simulation, to then integrate them in a real-time system, with the maximum number possible of high quality and natural looking animated agents. In order to accomplish our goal we present new techniques to achieve improvements in each one of these areas: In crowd simulation we work on a multi-domain planning approach and on planning using footsteps instead of just root velocities and positions; in animation we focus on a framework to eliminate foot sliding artifacts and on synthesizing motions of characters to follow footsteps; in rendering we provide novel techniques based on per joint impostors. Finally we present a novel framework to progressively integrate different methods for crowd simulation, animation and rendering. The framework offers level-of-detail for each of these areas, so that as new methods are integrated they can be combined efficiently to improve performance.