SCA: Eurographics/SIGGRAPH Symposium on Computer Animation

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Browsing SCA: Eurographics/SIGGRAPH Symposium on Computer Animation by Subject "agent systems"

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    Cognitive Model of Agent Exploration with Vision and Signage Understanding
    (The Eurographics Association and John Wiley & Sons Ltd., 2022) Johnson, Colin; Haworth, Brandon; Dominik L. Michels; Soeren Pirk
    Signage systems play an essential role in ensuring safe, stress-free, and efficient navigation for the occupants of indoor spaces. Crowd simulations with sufficiently realistic virtual humans provide a convenient and cost-effective approach to evaluating and optimizing signage systems. In this work, we develop an agent model which makes use of image processing on parametric saliency maps to visually identify signage and distractions in the agent's field of view. Information from identified signs is incorporated into a grid-based representation of wayfinding familiarity, which is used to guide informed exploration of the agent's environment using a modified A* algorithm. In areas with low wayfinding familiarity, the agent follows a random exploration behaviour based on sampling a grid of previously observed locations for heuristic values based on space syntax isovist measures. The resulting agent design is evaluated in a variety of test environments and found to be able to reliably navigate towards a goal location using a combination of signage and random exploration.
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    A Perceptually-Validated Metric for Crowd Trajectory Quality Evaluation
    (ACM, 2021) Daniel, Beatriz Cabrero; Marques, Ricardo; Hoyet, Ludovic; Pettré, Julien; Blat, Josep; Narain, Rahul and Neff, Michael and Zordan, Victor
    Simulating crowds requires controlling a very large number of trajectories and is usually performed using crowd motion algorithms for which appropriate parameter values need to be found. The study of the relation between parametric values for simulation techniques and the quality of the resulting trajectories has been studied either through perceptual experiments or by comparison with real crowd trajectories. In this paper, we integrate both strategies. A quality metric, QF, is proposed to abstract from reference data while capturing the most salient features that affect the perception of trajectory realism. QF weights and combines cost functions that are based on several individual, local and global properties of trajectories. These trajectory features are selected from the literature and from interviews with experts. To validate the capacity of QF to capture perceived trajectory quality, we conduct an online experiment that demonstrates the high agreement between the automatic quality score and non-expert users. To further demonstrate the usefulness of QF , we use it in a data-free parameter tuning application able to tune any parametric microscopic crowd simulation model that outputs independent trajectories for characters. The learnt parameters for the tuned crowd motion model maintain the influence of the reference data which was used to weight the terms of QF.