Fitting Behaviors to Pedestrian Simulations
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Date
2009
Journal Title
Journal ISSN
Volume Title
Publisher
ACM SIGGRAPH / Eurographics Association
Abstract
In this paper we present a data-driven approach for fitting behaviors to simulated pedestrian crowds. Our method annotates agent trajectories, generated by any crowd simulator, with action-tags. The aggregate effect of animating the agents according to the tagged trajectories enhances the impression that the agents are interacting with one another and with the environment. In a preprocessing stage, the stimuli which motivated a person to perform an action, as observed in a crowd video, are encoded into examples. Using the examples, non-linear, action specific influence functions are encoded into two-dimensional maps which evaluate, for each action, the relative importance of a stimulus within a configuration. At run time, given an agents stimuli configuration, the importance of each stimulus is determined and compared to the examples. Thus, the probability of performing each action is approximated and an action-tag is chosen accordingly. We fit behaviors to pedestrian crowds, thereby enhancing their natural appearance.
Description
@inproceedings{10.1145:1599470.1599496,
booktitle = {Eurographics/ ACM SIGGRAPH Symposium on Computer Animation},
editor = {Eitan Grinspun and Jessica Hodgins},
title = {{Fitting Behaviors to Pedestrian Simulations}},
author = {Lerner, Alon and Fitusi, Eitan and Chrysanthou, Yiorgos and Cohen-Or, Daniel},
year = {2009},
publisher = {ACM SIGGRAPH / Eurographics Association},
ISSN = {1727-5288},
ISBN = {978-1-60558-610-6},
DOI = {10.1145/1599470.1599496}
}