TY - JOUR
T1 - Crowds by example
AU - Lerner, Alon
AU - Chrysanthou, Yiorgos
AU - Lischinski, Dani
PY - 2007/9
Y1 - 2007/9
N2 - We present an example-based crowd simulation technique. Most crowd simulation techniques assume that the behavior exhibited by each person in the crowd can be defined by a restricted set of rules. This assumption limits the behavioral complexity of the simulated agents. By learning from real-world examples, our autonomous agents display complex natural behaviors that are often missing in crowd simulations. Examples are created from tracked video segments of real pedestrian crowds. During a simulation, autonomous agents search for examples that closely match the situation that they are facing. Trajectories taken by real people in similar situations, are copied to the simulated agents, resulting in seemingly natural behaviors.
AB - We present an example-based crowd simulation technique. Most crowd simulation techniques assume that the behavior exhibited by each person in the crowd can be defined by a restricted set of rules. This assumption limits the behavioral complexity of the simulated agents. By learning from real-world examples, our autonomous agents display complex natural behaviors that are often missing in crowd simulations. Examples are created from tracked video segments of real pedestrian crowds. During a simulation, autonomous agents search for examples that closely match the situation that they are facing. Trajectories taken by real people in similar situations, are copied to the simulated agents, resulting in seemingly natural behaviors.
UR - http://www.scopus.com/inward/record.url?scp=35348944859&partnerID=8YFLogxK
U2 - 10.1111/j.1467-8659.2007.01089.x
DO - 10.1111/j.1467-8659.2007.01089.x
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AN - SCOPUS:35348944859
SN - 0167-7055
VL - 26
SP - 655
EP - 664
JO - Computer Graphics Forum
JF - Computer Graphics Forum
IS - 3
ER -