Gradient‐based steering for vision‐based crowd simulation algorithms
Most recent crowd simulation algorithms equip agents with a synthetic vision component for steering. They offer promising perspectives through a more realistic simulation of the way humans navigate according to their perception of the surrounding environment. In this paper, we propose a new percepti...
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Published in | Computer graphics forum Vol. 36; no. 2; pp. 337 - 348 |
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Main Authors | , , , , |
Format | Journal Article |
Language | English |
Published |
Oxford
Blackwell Publishing Ltd
01.05.2017
Wiley |
Subjects | |
Online Access | Get full text |
ISSN | 0167-7055 1467-8659 |
DOI | 10.1111/cgf.13130 |
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Abstract | Most recent crowd simulation algorithms equip agents with a synthetic vision component for steering. They offer promising perspectives through a more realistic simulation of the way humans navigate according to their perception of the surrounding environment. In this paper, we propose a new perception/motion loop to steering agents along collision free trajectories that significantly improves the quality of vision‐based crowd simulators. In contrast with solutions where agents avoid collisions in a purely reactive (binary) way, we suggest exploring the full range of possible adaptations and retaining the locally optimal one. To this end, we introduce a cost function, based on perceptual variables, which estimates an agent's situation considering both the risks of future collision and a desired destination. We then compute the partial derivatives of that function with respect to all possible motion adaptations. The agent then adapts its motion by following the gradient. This paper has thus two main contributions: the definition of a general purpose control scheme for steering synthetic vision‐based agents; and the proposition of cost functions for evaluating the perceived danger of the current situation. We demonstrate improvements in several cases. |
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AbstractList | Most recent crowd simulation algorithms equip agents with a synthetic vision component for steering. They offer promising perspectives through a more realistic simulation of the way humans navigate according to their perception of the surrounding environment. In this paper, we propose a new perception/motion loop to steering agents along collision free trajectories that significantly improves the quality of vision‐based crowd simulators. In contrast with solutions where agents avoid collisions in a purely reactive (binary) way, we suggest exploring the full range of possible adaptations and retaining the locally optimal one. To this end, we introduce a cost function, based on perceptual variables, which estimates an agent's situation considering both the risks of future collision and a desired destination. We then compute the partial derivatives of that function with respect to all possible motion adaptations. The agent then adapts its motion by following the gradient. This paper has thus two main contributions: the definition of a general purpose control scheme for steering synthetic vision‐based agents; and the proposition of cost functions for evaluating the perceived danger of the current situation. We demonstrate improvements in several cases. Most recent crowd simulation algorithms equip agents with a synthetic vision component for steering. They offer promising perspectives through a more realistic simulation of the way humans navigate according to their perception of the surrounding environment. In this paper, we propose a new perception/motion loop to steering agents along collision free trajectories that significantly improves the quality of vision-based crowd simulators. In contrast with solutions where agents avoid collisions in a purely reactive (binary) way, we suggest exploring the full range of possible adaptations and retaining the locally optimal one. To this end, we introduce a cost function, based on perceptual variables, which estimates an agent’s situation considering both the risks of future collision and a desired destination. We then compute the partial derivatives of that function with respect to all possible motion adaptations. The agent then adapts its motion by following the gradient. This paper has thus two main contributions: the definition of a general purpose control scheme for steering synthetic vision-based agents; and the proposition of cost functions for evaluating the perceived danger of the current situation. We demonstrate improvements in several cases. T. B. Dutra acknowl1edges CAPES for the fellowship (PDSE Proc. 0130/13-3) and J. Ondˇrej for helping in the implementation of his model. R. Marques acknowledges the projects Percolation (ANR- 13-JS02-0008), and Kristina (H2020-RIA-645012) for partially financing this research. |
Author | Vidal, C. A. Pettré, J. Cavalcante‐Neto, J.B. Dutra, T. B. Marques, R. |
Author_xml | – sequence: 1 givenname: T. B. surname: Dutra fullname: Dutra, T. B. – sequence: 2 givenname: R. surname: Marques fullname: Marques, R. – sequence: 3 givenname: J.B. surname: Cavalcante‐Neto fullname: Cavalcante‐Neto, J.B. – sequence: 4 givenname: C. A. surname: Vidal fullname: Vidal, C. A. – sequence: 5 givenname: J. surname: Pettré fullname: Pettré, J. |
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Copyright | 2017 The Author(s) Computer Graphics Forum © 2017 The Eurographics Association and John Wiley & Sons Ltd. Published by John Wiley & Sons Ltd. 2017 The Eurographics Association and John Wiley & Sons Ltd. info:eu-repo/semantics/openAccess This is the peer reviewed version of the following article: Dutra TB, Marques R, Cavalcante-Neto JB, Vidal CA, Pettré J. Gradient-based steering for vision-based crowd simulation algorithms. Comput Graph Forum. 2017;36:337-48, which has been published in final form at http://dx.doi.org/10.1111/cgf.13130 This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving. Distributed under a Creative Commons Attribution 4.0 International License |
Copyright_xml | – notice: 2017 The Author(s) Computer Graphics Forum © 2017 The Eurographics Association and John Wiley & Sons Ltd. Published by John Wiley & Sons Ltd. – notice: 2017 The Eurographics Association and John Wiley & Sons Ltd. – notice: info:eu-repo/semantics/openAccess This is the peer reviewed version of the following article: Dutra TB, Marques R, Cavalcante-Neto JB, Vidal CA, Pettré J. Gradient-based steering for vision-based crowd simulation algorithms. Comput Graph Forum. 2017;36:337-48, which has been published in final form at <a href="http://dx.doi.org/10.1111/cgf.13130">http://dx.doi.org/10.1111/cgf.13130</a> This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving. – notice: Distributed under a Creative Commons Attribution 4.0 International License |
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Snippet | Most recent crowd simulation algorithms equip agents with a synthetic vision component for steering. They offer promising perspectives through a more realistic... Most recent crowd simulation algorithms equip agents with a synthetic vision component for steering. They offer promising perspectives through a more realistic... |
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SubjectTerms | Algorithms Animation Categories and Subject Descriptors (according to ACM CCS) Collision avoidance Collision dynamics Computer Science Computer simulation Cost function Crowds Enhanced vision Graphics Hazards I.3.7 [Computer Graphics]: Three‐Dimensional Graphics and Realism—Animation I.6.5 [Simulation and Modeling]: Types of Simulation—Animation Navigation Perception Simulation Simulators Steering Three-dimensional graphics and realism Types of simulation Vision systems |
Title | Gradient‐based steering for vision‐based crowd simulation algorithms |
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