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This article by authors Soraia Raupp Musse and Daniel Thalmann, published in 2001, presents a hierarchical ViCrowd framework for real-time simulation of virtual human crowds. It explores scripted, reactive, and user-guided behaviors in controlling crowds, emphasizing knowledge, beliefs, and intentions. The article discusses crowd modeling challenges, different crowd control types, and ViCrowd structure to enable group interactions in real-time simulations. It also highlights related work on behaviors like flocking, following, goal changing, attraction, repulsion, split, space adaptability, and safe-wandering. Future work includes enhancing the ViCrowd script language with Python and implementing panic and emergency behaviors.
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Bart van Greevenbroek Hierarchical Model for Real Time Simulation of Virtual HumanCrowds
Overview • Article • Authors • ViCrowd • Experiments • Assessment
The Authors SoraiaRauppMusse Daniel Thalmann
The Article • Published in 2001 • Cited 229 times • Cited by “Finding Paths for Coherent Groups Using clearance” (no 6 on our list) by Arno kamphuis and Mark Overmars
Controlling a Crowd • Scripted behaviors • Reactive behaviors • User-guided behaviors
ViCrowd • Behavioral based multi-level framework • Used to simulate crowds in real time • Script-based language.
Knowledge, Beliefs and Intentions • Knowledge (information about the world) • Beliefs (states of emotion) • Intentions (goals)
Events • Can change the knowledge, beliefs or intentions of an agent • And thus the behavior • Example: A door closes, the knowledge that the door closes changes, agents will not go through that door. • Example: A bomb goes off, agents within a radius panic, and behavior is altered.
Main Problems • Modeling of crowd information, also concerning the distribution of groups • Different levels of realism • Required Structure to provide interaction between groups of agents in real time
High level • Flocking • Following • Goal Changing • Attraction • Repulsion • Split • Space adaptability • Safe-Wandering
Flocking • the agents from the same group share the same list of goals; • They walk at similar speeds; • They follow the paths generated as showed • One agent can wait for another on arrival at a goal when another agent from the same group is missing.
Following • A group can follow another group by sharing the same goals, either temporary or permanently.
Goal Changing • Agents can change groups, and this is influenced by the relationship value with each agent in the group (value between 0 and 1) • Agents have a leadership ability value, which is also taken into account • If an agent has a higher relationship with another group, it will join that group. If the leadership value is high enough
Attraction • The user can paint regions where the groups must be at a certain point, and the orientation can be influenced as well. • Groups are normally attracted to attraction points
Repulsion • Groups are repulsed by obstacles and each other (similar to the social force model)
Split • Groups can split randomly
Space Adaptability • The group wants to occupy all the walking space, using a bezier curve:
Safe-Wandering • Using a procedural method, the agents predict collisions using collision detection between two lines
Results (1) • Scripted Behavior (SB) • Reactive Behavior (RB) • Guided Behavior (GB)
Future work • Improving viCrowd script language by integrating Python • Panic and Emergency Behaviors
The Good • High level of compatibility with other methods • Very flexible system • User has control over groups if needed • Groups are essential for a realistic crowd, so its good to focus on groups • Knowledge, Beliefs and Intentions is a well-known paradigm in the AI field
The Bad • Performance is not awe-inspiring • Exact formulae are missing • No system specs are given, which makes comparison with other methods difficult • A collection of simple motions are possible, but what about complex motions? • Seeing as groups follow attraction points, Oscillations can occur.
The ugly • The site with examples they mentioned, does not work. • Figures are sloppy, some text is cut off. • Meaningless pictures. If something is happening in the experiment involving motions, draw arrows or make the motion obvious. • In general, they go all over the place.