From audiences to mobs : crowd simulation with psychological factors
Author(s)
Advisor
Date
2010Publisher
Bilkent University
Language
English
Type
ThesisItem Usage Stats
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Abstract
Crowd simulation has a wide range of application areas such as biological
and social modeling, military simulations, computer games and movies. Simulating
the behavior of animated virtual crowds has been a challenging task for the
computer graphics community. As well as the physical and the geometrical aspects,
the semantics underlying the motion of real crowds inspire the design and
implementation of virtual crowds. Psychology helps us understand the motivations
of the individuals constituting a crowd. There has been extensive research
on incorporating psychological models into the simulation of autonomous agents.
However, in our study, instead of the psychological state of an individual agent as
such, we are interested in the overall behavior of the crowd that consists of virtual
humans with various psychological states. For this purpose, we incorporate the
three basic constituents of affect: personality, emotion and mood. Each of these
elements contribute variably to the emergence of different aspects of behavior.
We thus examine, by changing the parameters, how groups of people with different
characteristics interact with each other, and accordingly, how the global
crowd behavior is influenced.
In the social psychology literature, crowds are classified as mobs and audiences.
Audiences are passive crowds whereas mobs are active crowds with emotional,
irrational and seemingly homogeneous behavior. In this thesis, we examine
how audiences turn into mobs and simulate the common properties of mobs to
create collective misbehavior. So far, crowd simulation research has focused on
panicking crowds among all types of mobs. We extend the state of the art to simulate
different types of mobs based on the taxonomy. We demonstrate various
scenarios that realize the behavior of distinct mob types.
Our model is built on top of an existing crowd simulation system, HiDAC
(High-Density Autonomous Crowds). HiDAC provides us with the physical and
low-level psychological features of crowds. The user normally sets these parameters
to model the non-uniformity and diversity of the crowd. In our work, we
free the user of the tedious task of low-level parameter tuning, and combine all
these behaviors in distinct psychological factors. We present the results of our
experiments on whether the incorporation of a personality model into HiDAC
was perceived as intended.