Inferring a User's Intent on Joining or Passing by Social Groups

Bönsch, Andrea; Bluhm, Alexander R.; Ehret, Jonathan; Kuhlen, Torsten

doi:10.1145/3383652.3423862

Cited by 5 publications

(2 citation statements)

References 38 publications

(88 reference statements)

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“…By tuning these parameters, designers have some control over how agents behave, but this tuning is not always intuitive and requires expert knowledge of the simulation model. To improve this, several researchers have proposed systems where a user can interactively edit parameters while the simulation is running [MR05; MMHR16], possibly even by immersing the user into the simulation itself [BBEK20]. Other work has explored ways to automatically tune simulation parameters to match particular data, such as quantitative metrics [WGO∗14], controlled randomization [NLS14], textual descriptions [CWL20; LWC20], and start and goal positions of agents [ACC14].…”

Section: Related Workmentioning

confidence: 99%

“…Various methods exist that try to give users more intuitive control over a crowd via sketch‐based techniques. Most of these provide control over global paths , by letting users draw curves for agents to follow [UdHT04; KSA∗09; OO09; MM17; BBEK20] or directional hints that are converted to a flow field [PWJ∗08; PvdBC∗11; KK∗14]. Some of these methods also propose sketch‐based control of other simulation parameters, such as the walking speed and the smoothness of paths [UdHT04; OO09].…”

Section: Related Workmentioning

confidence: 99%

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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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