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
ACM SIGGRAPH 2006 Papers
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
A decision network framework for the behavioral animation of virtual humans
SCA '07 Proceedings of the 2007 ACM SIGGRAPH/Eurographics symposium on Computer animation
Clone attack! Perception of crowd variety
ACM SIGGRAPH 2008 papers
Being a part of the crowd: towards validating VR crowds using presence
Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 1
Creating crowd variation with the OCEAN personality model
Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 3
Experiment-based modeling, simulation and validation of interactions between virtual walkers
Proceedings of the 2009 ACM SIGGRAPH/Eurographics Symposium on Computer Animation
Aggregate dynamics for dense crowd simulation
ACM SIGGRAPH Asia 2009 papers
SteerBench: a benchmark suite for evaluating steering behaviors
Computer Animation and Virtual Worlds - International Workshop Motion in Games (MIG08)
A Predictive Collision Avoidance Model for Pedestrian Simulation
MIG '09 Proceedings of the 2nd International Workshop on Motion in Games
Data Driven Evaluation of Crowds
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
Perceptual effects of scene context and viewpoint for virtual pedestrian crowds
ACM Transactions on Applied Perception (TAP)
Directing Crowd Simulations Using Navigation Fields
IEEE Transactions on Visualization and Computer Graphics
PLEdestrians: a least-effort approach to crowd simulation
Proceedings of the 2010 ACM SIGGRAPH/Eurographics Symposium on Computer Animation
Simulating heterogeneous crowd behaviors using personality trait theory
SCA '11 Proceedings of the 2011 ACM SIGGRAPH/Eurographics Symposium on Computer Animation
Scenario space: characterizing coverage, quality, and failure of steering algorithms
SCA '11 Proceedings of the 2011 ACM SIGGRAPH/Eurographics Symposium on Computer Animation
Tracking Pedestrians Using Local Spatio-Temporal Motion Patterns in Extremely Crowded Scenes
IEEE Transactions on Pattern Analysis and Machine Intelligence
Crowd Light: Evaluating the Perceived Fidelity of Illuminated Dynamic Scenes
Computer Graphics Forum
ACM Transactions on Graphics (TOG) - SIGGRAPH 2013 Conference Proceedings
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We present an information-theoretic method to measure the similarity between a given set of observed, real-world data and visual simulation technique for aggregate crowd motions of a complex system consisting of many individual agents. This metric uses a two-step process to quantify a simulator's ability to reproduce the collective behaviors of the whole system, as observed in the recorded real-world data. First, Bayesian inference is used to estimate the simulation states which best correspond to the observed data, then a maximum likelihood estimator is used to approximate the prediction errors. This process is iterated using the EM-algorithm to produce a robust, statistical estimate of the magnitude of the prediction error as measured by its entropy (smaller is better). This metric serves as a simulator-to-data similarity measurement. We evaluated the metric in terms of robustness to sensor noise, consistency across different datasets and simulation methods, and correlation to perceptual metrics.