Flocks, herds and schools: A distributed behavioral model
SIGGRAPH '87 Proceedings of the 14th annual conference on Computer graphics and interactive techniques
Cognitive modeling: knowledge, reasoning and planning for intelligent characters
Proceedings of the 26th annual conference on Computer graphics and interactive techniques
Proceedings of the 2005 ACM SIGGRAPH/Eurographics symposium on Computer animation
Tutorial on agent-based modeling and simulation
WSC '05 Proceedings of the 37th conference on Winter simulation
Controlling individual agents in high-density crowd simulation
SCA '07 Proceedings of the 2007 ACM SIGGRAPH/Eurographics symposium on Computer animation
Group behavior from video: a data-driven approach to crowd simulation
SCA '07 Proceedings of the 2007 ACM SIGGRAPH/Eurographics symposium on Computer animation
Experiment-based modeling, simulation and validation of interactions between virtual walkers
Proceedings of the 2009 ACM SIGGRAPH/Eurographics Symposium on Computer Animation
A Predictive Collision Avoidance Model for Pedestrian Simulation
MIG '09 Proceedings of the 2nd International Workshop on Motion in Games
A synthetic-vision based steering approach for crowd simulation
ACM SIGGRAPH 2010 papers
Crowd modeling and simulation technologies
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Simulating and Evaluating the Local Behavior of Small Pedestrian Groups
IEEE Transactions on Visualization and Computer Graphics
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With the development of Computer Graphics and Virtual Reality technology, crowds in the virtual worlds have become increasingly lively and appealing. However, few existing methods take into account that pedestrians usually walk in small groups of twos and threes in real life, for instance, shopping couples and partners. Our research is based on dynamic behavior of small groups and the interaction between them. By using synthetic-vision based steering approach, combining with formation characteristics and deformation mode of small groups, we propose an approach to simulate the local behavior of small groups. Experiments show that our method can reproduce the local behavior of small groups in real life.