Semantic Crowd Re-targeting: Implementation for Real-time Applications and User Evaluations

摘要

Crowd simulation is the act of simulating and controlling the dynamic movement of large groups of virtual characters. Crowd simulation is traditionally a complex and time-consuming process, requiring extensive manual effort to achieve. On the one hand, commercial and liberally licensed tools tend to have many aspects of simulation tightly integrated which can be prohibitively difficult to re-configure, on the other, paying extras can be far more costly. In this context, the re-use of existing simulated crowds has been identified as a valuable cost-saving approach to crowd simulations. Previous approaches have investigated the use of environment semantics, but they have not been integrated with a commonly used simulation platform, rendering their usefulness limited. We present a novel approach to crowd simulation using an emergent system for re-targeting autonomous crowds and report on the findings of a problem discovery study, analyzing and establishing key aspects of functionality, usability, and user experience. Our results provide a breakdown of the crowd simulation process with corresponding time-on-task metrics to provide a reference point for future scientific research into crowd simulation systems. Furthermore, we report on how users react to a system that involves the use of semantic data to facilitate the re-use of existing crowd simulations. We anticipate that other researchers will follow suit, to develop tools that are both innovative and usable in crowd simulation practices.