Issue No.05 - Sept.-Oct. (2011 vol.31)
Zhigang Deng , Comput. Graphics & Interactive Media Lab., Univ. of Houston, Houston, TX, USA
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/MCG.2010.38
Traditional crowd simulation models typically focus on navigational pathfinding and local collision avoidance. Little research has explored how to optimally control individual agents' detailed motions throughout a crowd. A proposed approach dynamically controls agents' motion styles to increase a crowd's motion variety. The central idea is to maximize both the style variety of local neighbors and global style utilization while maintaining a consistent style for each agent that's as natural as possible. To assist runtime diversity control, an offline preprocessing algorithm extracts primitive motions from a motion capture database and stylizes them. This approach can complement most high-level crowd models to increase realistic variety. Four experiment scenarios and a user evaluation demonstrate this approach's superior flexibility compared to traditional random distribution of motion styles. The Web extra is a video demonstrating a military-march simulation.
Context modeling, Computational modeling, Motion control, Computer simulation, Navigation, Collision avoidance, Computer science,and user study, crowd simulation, motion diversification, motion variety, variety realism, character animation
Zhigang Deng, "Context-Aware Motion Diversification for Crowd Simulation", IEEE Computer Graphics and Applications, vol.31, no. 5, pp. 54-65, Sept.-Oct. 2011, doi:10.1109/MCG.2010.38