Agent-based approaches for stylizing motion variations and formations in crowd simulation

Crowd simulation is the process of simulating the movement of a large number of objects or autonomous characters. Animating large-scale crowds has emerged in recent years as a challenging problem in film, game, virtual training, and education applications. Traditional crowd simulation approaches typically focus on navigational path-finding and local collision avoidance problems using steering rules and social forces, which are able to successfully synthesize the local movement trajectory of each crowd agent. However, relatively few existing efforts explore how to optimally control individual agents' detailed motions and global strategic formations throughout a crowd. Therefore, the main goal of this dissertation is to propose an agent-based framework for embedding realistic motion variations and group formation behaviors into crowd simulations.;When we apply the animation control scheme above, the perception of motion transitions in a pedestrian crowd is affected by many collective features such as crowd density, appearance variations, motion variations, and sub-group interaction patterns. We conducted a series of psychophysical experiments to investigate how these crowd features can influence human perception on walking motion transitions in a crowd when inexpensive motion blending algorithms are used.;In the high-level crowd behavior simulations, collective group formations are often manually specified via various hard constraints such as pre-defined key-frames of the exact agent distribution. Instead, the global configurations of different group formations in our framework are parameterized from arbitrary user sketches, which are interactively specified during the simulations. In other words, we propose an intuitive yet efficient approach to generate group formations by sketching formation boundaries. Our approach can automatically compute the desired positions for each agent in the target formation and generate the agent correspondences between key-frames.;In the low-level simulations, the key idea of adding variation of agent motions is to dynamically control motion styles of agents through maximizing the style variety of local neighbors and universal style utilization while keeping the style consistency for each agent as natural as possible. Our scheme can serve as a complementary layer for most high-level crowd models to increase the realism of a simulated crowd.