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SteerBug: an interactive framework for specifying and detecting steering behaviors

Published: 01 August 2009 Publication History

Abstract

The size of crowds that modern computer games and urban simulations are capable of handling has given rise to the challenging problem of debugging and testing massive simulations of autonomous agents. In this paper, we propose SteerBug: an interactive framework for specifying and detecting steering behaviors. Our framework computes a set of time-varying metrics for agents and their environment, which characterize steering behaviors. We identify behaviors of interest by applying conditions (rules) or user defined sketches on the associated metrics. The behaviors we can specify and detect include unnatural steering, plainly incorrect results, or application-specific behaviors of interest. Our framework is extensible and independent of the specifics of any steering approach. To our knowledge, this is the first work that aims to provide a computational framework for specifying and detecting crowd behaviors in animation.

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      cover image ACM Conferences
      SCA '09: Proceedings of the 2009 ACM SIGGRAPH/Eurographics Symposium on Computer Animation
      August 2009
      258 pages
      ISBN:9781605586106
      DOI:10.1145/1599470
      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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      Published: 01 August 2009

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      • (2023)Debugging Video Games: A Systematic MappingProceedings of the 1st ACM International Workshop on Future Debugging Techniques10.1145/3605155.3605865(23-30)Online publication date: 17-Jul-2023
      • (2023)Sketching Vocabulary for Crowd MotionComputer Graphics Forum10.1111/cgf.1462941:8(119-130)Online publication date: 20-Mar-2023
      • (2023)Heterogeneous Crowd Simulation Using Parametric Reinforcement LearningIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2021.313903129:4(2036-2052)Online publication date: 1-Apr-2023
      • (2022)Authoring Virtual Crowds: A SurveyComputer Graphics Forum10.1111/cgf.1450641:2(677-701)Online publication date: 24-May-2022
      • (2022)Interaction Fields: Intuitive Sketch‐based Steering Behaviors for Crowd SimulationComputer Graphics Forum10.1111/cgf.1449141:2(521-534)Online publication date: 24-May-2022
      • (2021)Perceived Realism of Pedestrian Crowds Trajectories in VRProceedings of the 27th ACM Symposium on Virtual Reality Software and Technology10.1145/3489849.3489860(1-5)Online publication date: 8-Dec-2021
      • (2021)A Perceptually-Validated Metric for Crowd Trajectory Quality EvaluationProceedings of the ACM on Computer Graphics and Interactive Techniques10.1145/34801364:3(1-18)Online publication date: 27-Sep-2021
      • (2020)Interactive Inverse Spatio-Temporal Crowd Motion DesignSymposium on Interactive 3D Graphics and Games10.1145/3384382.3384528(1-9)Online publication date: 5-May-2020
      • (2018)Crowd spaceACM Transactions on Graphics10.1145/3272127.327507937:6(1-14)Online publication date: 4-Dec-2018
      • (2017)Implicit crowdsACM Transactions on Graphics10.1145/3072959.307370536:4(1-13)Online publication date: 20-Jul-2017
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