Crowd art

Jordao, Kevin; Charalambous, Panayiotis; Christie, Marc; Pettré, Julien; Cani, Marie-Paule

doi:10.1145/2822013.2822023

Cited by 11 publications

(6 citation statements)

References 30 publications

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“…In the case of an accident, the critical density in Kerman bazaar will be created in about 1 minute 10 seconds after the event. Jordao et al 16 estimated the critical gathering point around Wall Street in New York City at about 5000 people, which is consistent with the present study given the extent and area of the passages in comparison to the Kerman bazaar. Shendarkar et al 17 simulated crowd evacuation in Washington, DC, by using the BDI (belief, desire, intention) model.…”

Section: Discussionsupporting

confidence: 91%

Crowd Simulations and Determining the Critical Density Point of Emergency Situations

Khademipour

Nakhaee

Anari

et al. 2017

Disaster med. public health prep.

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Section: Discussionsupporting

confidence: 91%

Crowd Simulations and Determining the Critical Density Point of Emergency Situations

Khademipour

Nakhaee

Anari

et al. 2017

Disaster med. public health prep.

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“…Another set of solutions is more oriented towards editing existing crowd motion clips to adapt to new situations. Following up on the concept of ‘crowd patches’ that can be stitched together [YMPT09], there are several methods that let users intuitively deform crowd motion clips to create crowds of different shapes [JPCC14; KSKL14; KL16] or densities [JCC∗15]. There is also a line of work that models a crowd as a deformable mesh, to steer it efficiently along (user‐specified) paths in the presence of obstacles [KLLT08; HSK12; HSK14; ZZZY20].…”

Section: Related Workmentioning

confidence: 99%

Interaction Fields: Intuitive Sketch‐based Steering Behaviors for Crowd Simulation

Colas

Toll

Zibrek

et al. 2022

Computer Graphics Forum

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The real‐time simulation of human crowds has many applications. In a typical crowd simulation, each person ('agent') in the crowd moves towards a goal while adhering to local constraints. Many algorithms exist for specific local ‘steering’ tasks such as collision avoidance or group behavior. However, these do not easily extend to completely new types of behavior, such as circling around another agent or hiding behind an obstacle. They also tend to focus purely on an agent's velocity without explicitly controlling its orientation. This paper presents a novel sketch‐based method for modelling and simulating many steering behaviors for agents in a crowd. Central to this is the concept of an interaction field (IF): a vector field that describes the velocities or orientations that agents should use around a given ‘source’ agent or obstacle. An IF can also change dynamically according to parameters, such as the walking speed of the source agent. IFs can be easily combined with other aspects of crowd simulation, such as collision avoidance. Using an implementation of IFs in a real‐time crowd simulation framework, we demonstrate the capabilities of IFs in various scenarios. This includes game‐like scenarios where the crowd responds to a user‐controlled avatar. We also present an interactive tool that computes an IF based on input sketches. This IF editor lets users intuitively and quickly design new types of behavior, without the need for programming extra behavioral rules. We thoroughly evaluate the efficacy of the IF editor through a user study, which demonstrates that our method enables non‐expert users to easily enrich any agent‐based crowd simulation with new agent interactions.

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“…These traits affect various levels of crowd simulation, in addition to the high‐level behaviours component; the HiDAC model [PAB07] directly affects path‐planning. Desires of being close to other agents are also incorporated in some path‐planning systems like Crowd art [JCC*15].…”

Section: High‐level Behavioursmentioning

confidence: 99%

“…Crowd Patches also enable temporally controlling the agents, in the sense of defining when the agents enter and exit a certain patch. The concept of crowd patches has been utilised in further research ([JPCC14,JCC*15]). Crowd Sculpting by [JPCC14] introduces and integrates space‐time mutable elastic models, yielding an authoring tool for creating large, endless, moving crowds.…”

Section: Path‐planningmentioning

confidence: 99%

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Authoring Virtual Crowds: A Survey

Lemonari

Blanco

Charalambous

et al. 2022

Computer Graphics Forum

Self Cite

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Recent advancements in crowd simulation unravel a wide range of functionalities for virtual agents, delivering highly-realistic, natural virtual crowds. Such systems are of particular importance to a variety of applications in fields such as: entertainment (e.g., movies, computer games); architectural and urban planning; and simulations for sports and training. However, providing their capabilities to untrained users necessitates the development of authoring frameworks. Authoring virtual crowds is a complex and multi-level task, varying from assuming control and assisting users to realise their creative intents, to delivering intuitive and easy to use interfaces, facilitating such control. In this paper, we present a categorisation of the authorable crowd simulation components, ranging from high-level behaviours and path-planning to local movements, as well as animation and visualisation. We provide a review of the most relevant methods in each area, emphasising the amount and nature of influence that the users have over the final result. Moreover, we discuss the currently available authoring tools (e.g., graphical user interfaces, drag-and-drop), identifying the trends of early and recent work. Finally, we suggest promising directions for future research that mainly stem from the rise of learning-based methods, and the need for a unified authoring framework.

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Crowd art

Abstract: Figure 1: Our system can be used to populate a large city like environment such as the Wall Street area in New York with crowds of different density and direction constraints in minutes. Resulting crowd motion can then be played endlessly always satisfying the user's intent.

Cited by 11 publications

References 30 publications

Crowd Simulations and Determining the Critical Density Point of Emergency Situations

Crowd Simulations and Determining the Critical Density Point of Emergency Situations

Interaction Fields: Intuitive Sketch‐based Steering Behaviors for Crowd Simulation

Authoring Virtual Crowds: A Survey

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