Browsing by Subject "Crowd simulation"

Now showing 1 - 19 of 19

Open Access
ACMICS: an agent communication model for interacting crowd simulation
(Springer, 2017) Kullu, K.; Güdükbay, Uğur; Manocha, D.
Behavioral plausibility is one of the major aims of crowd simulation research. We present a novel approach that simulates communication between the agents and assess its influence on overall crowd behavior. Our formulation uses a communication model that tends to simulate human-like communication capability. The underlying formulation is based on a message structure that corresponds to a simplified version of Foundation for Intelligent Physical Agents Agent Communication Language Message Structure Specification. Our algorithm distinguishes between low- and high-level communication tasks so that ACMICS can be easily extended and employed in new simulation scenarios. We highlight the performance of our communication model on different crowd simulation scenarios. We also extend our approach to model evacuation behavior in unknown environments. Overall, our communication model has a small runtime overhead and can be used for interactive simulation with tens or hundreds of agents. © 2017, The Author(s).
Open Access
ACMICS: An agent communication model for interacting crowd simulation: JAAMAS track
(International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS), 2018) Kullu, K.; Güdükbay, Uğur; Manocha, D.
We present and evaluate a novel approach to simulate communication between the agents. Our approach distinguishes low- And high-level communication tasks. This separation makes it easy to extend and use it in new scenarios. We highlight the benefits of our approach using different simulation scenarios consisting of hun-dreds of agents. We also model evacuation behavior in unknown environments and highlight the benefits of our approach particularly in simulating such behavior.
Open Access
Adaptive grids: an image-based approach to generate navigation meshes
(S P I E - International Society for Optical Engineering, 2013-02-01) Akaydın, A.; Güdükbay, U.
We propose adaptive grids, an image-based approach for constructing navigation meshes, which are used for path planning. A cellular navigation mesh, called an adaptive grid, is constructed from a top-view range image of a three-dimensional urban model. A navigation graph can then be extracted from this adaptive grid for path planning. We compare our approach with two popular navigation mesh-generation approaches and obtain promising results in terms of path accuracy and memory cost.
Open Access
Augmentation of virtual agents in real crowd videos
(Springer, 2019) Doğan, Yalım; Demirci, Serkan; Güdükbay, Uğur; Dibeklioğlu, Hamdi
Augmenting virtual agents in real crowd videos is an important task for different applications from simulations of social environments to modeling abnormalities in crowd behavior. We propose a framework for this task, namely for augmenting virtual agents in real crowd videos. We utilize pedestrian detection and tracking algorithms to automatically locate the pedestrians in video frames and project them into our simulated environment, where the navigable area of the simulated environment is available as a navigation mesh. We represent the real pedestrians in the video as simple three-dimensional (3D) models in our simulation environment. 3D models representing real agents and the augmented virtual agents are simulated using local path planning coupled with a collision avoidance algorithm. The virtual agents augmented into the real video move plausibly without colliding with static and dynamic obstacles, including other virtual agents and the real pedestrians.
Open Access
An augmented crowd simulation system using automatic determination of navigable areas
(Elsevier Ltd, 2021-04) Doğan, Yalım; Sonlu, Sinan; Güdükbay, Uğur
Crowd simulations imitate the group dynamics of individuals in different environments. Applications in entertainment, security, and education require augmenting simulated crowds into videos of real people. In such cases, virtual agents should realistically interact with the environment and the people in the video. One component of this augmentation task is determining the navigable regions in the video. In this work, we utilize semantic segmentation and pedestrian detection to automatically locate and reconstruct the navigable regions of surveillance-like videos. We place the resulting flat mesh into our 3D crowd simulation environment to integrate virtual agents that navigate inside the video avoiding collision with real pedestrians and other virtual agents. We report the performance of our open-source system using real-life surveillance videos, based on the accuracy of the automatically determined navigable regions and camera configuration. We show that our system generates accurate navigable regions for realistic augmented crowd simulations.
Open Access
Communication models for crowd simulation
(2017-07) Küllü, Kurtuluş
Modeling and animation of behaviorally plausible virtual crowds are important problems of crowd simulation research. We propose a communication model in order to equip virtual agents with the ability to autonomously communicate with each other. We investigate whether such a communication model would improve the plausibility of the simulated crowds. Initially, our efforts were towards a model that is as human-like as possible and towards combining this model with an agent architecture that contains psychological attributes. Early experimental results showed that when we look at a crowd, the influences such as different agent personalities causing different communicative behavior are hardly visible. Besides, achieving these effects introduces complexity. Thus, a generic and easyto- use communication model instead of a human-like one became the target and psychological agent attributes were dropped. The proposed communication model and its application in several scenarios are presented in this dissertation. As a second contribution, one of the application scenarios led us to develop a planning algorithm for an agent in an unknown environment. Simulation results are analyzed both visually and by using various measurements and metrics. Our conclusion is that in addition to improving observed behavioral variety, the effects of employing the communication model are clear in the quantitative results and these effects are in line with our expectations in each scenario.
Open Access
Creating crowd variation with the OCEAN personality model
(IFAAMAS, 2008-05) Durupınar, Funda; Allbeck, J.; Pelechano, N.; Badler, N.
Most current crowd simulators animate homogeneous crowds, but include underlying parameters that can be tuned to create variations within the crowd. These parameters, however, are specific to the crowd models and may be difficult for an animator or naive user to use. We propose mapping these parameters to personality traits. In this paper, we extend the HiDAC (High-Density Autonomous Crowds) system by providing each agent with a personality model in order to examine how the emergent behavior of the crowd is affected. We use the OCEAN personality model as a basis for agent psychology. To each personality trait we associate nominal behaviors; thus, specifying personality for an agent leads to an automation of the low-level parameter tuning process. We describe a plausible mapping from personality traits to existing behavior types and analyze the overall emergent crowd behaviors. Copyright © 2008, International Foundation for Autonomous Agents and Multiagent Systems (www.ifaamas.org). All rights reserved.
Open Access
Dynamic point-region quadtrees for particle simulations
(Elsevier Inc., 2013) Oğuz, O.; Durupınar, F.; Güdükbay, Uğur
We propose an algorithm for dynamically updating point-region (PR) quadtrees. Our algorithm is optimized for simultaneous update of data points comprising a quadtree. The intended application area focuses on simulating continuum phenomena, such as crowds, fluids, and smoke. We minimize the number of tree updates by making use of small changes in the positions of data points. We compare the efficiency of the proposed algorithm with two other approaches for updating a quadtree. One of these techniques creates the tree from scratch at each time-step. The second technique subsequently deletes a data point from the tree and reinserts it in its updated position. We achieve significant performance gains with our method in both cases. © 2012 Elsevier Inc. All rights reserved.
Open Access
Emergency crowd simulation for outdoor environments
(Pergamon Press, 2010) Oğuz, O.; Akaydın, A.; Yilmaz, T.; Güdükbay, Uğur
We simulate virtual crowds in emergency situations caused by an incident, such as a fire, an explosion, or a terrorist attack. We use a continuum dynamics-based approach to simulate the escaping crowd, which produces more efficient simulations than the agent-based approaches. Only the close proximity of the incident region, which includes the crowd affected by the incident, is simulated. We use a model-based rendering approach where a polygonal mesh is rendered for each agent according to the agent's skeletal motion. To speed up the animation and visualization, we employ an offline occlusion culling technique. We animate and render a pedestrian model only if it is visible according to the static visibility information computed. In the pre-processing stage, the navigable area is decomposed into a grid of cells and the from-region visibility of these cells is computed with the help of hardware occlusion queries. © 2009 Elsevier Ltd. All rights reserved.
Open Access
From audiences to mobs : crowd simulation with psychological factors
(2010) Durupınar, Funda
Crowd simulation has a wide range of application areas such as biological and social modeling, military simulations, computer games and movies. Simulating the behavior of animated virtual crowds has been a challenging task for the computer graphics community. As well as the physical and the geometrical aspects, the semantics underlying the motion of real crowds inspire the design and implementation of virtual crowds. Psychology helps us understand the motivations of the individuals constituting a crowd. There has been extensive research on incorporating psychological models into the simulation of autonomous agents. However, in our study, instead of the psychological state of an individual agent as such, we are interested in the overall behavior of the crowd that consists of virtual humans with various psychological states. For this purpose, we incorporate the three basic constituents of affect: personality, emotion and mood. Each of these elements contribute variably to the emergence of different aspects of behavior. We thus examine, by changing the parameters, how groups of people with different characteristics interact with each other, and accordingly, how the global crowd behavior is influenced. In the social psychology literature, crowds are classified as mobs and audiences. Audiences are passive crowds whereas mobs are active crowds with emotional, irrational and seemingly homogeneous behavior. In this thesis, we examine how audiences turn into mobs and simulate the common properties of mobs to create collective misbehavior. So far, crowd simulation research has focused on panicking crowds among all types of mobs. We extend the state of the art to simulate different types of mobs based on the taxonomy. We demonstrate various scenarios that realize the behavior of distinct mob types. Our model is built on top of an existing crowd simulation system, HiDAC (High-Density Autonomous Crowds). HiDAC provides us with the physical and low-level psychological features of crowds. The user normally sets these parameters to model the non-uniformity and diversity of the crowd. In our work, we free the user of the tedious task of low-level parameter tuning, and combine all these behaviors in distinct psychological factors. We present the results of our experiments on whether the incorporation of a personality model into HiDAC was perceived as intended.
Open Access
A group-based approach for gaze behavior of virtual crowds incorporating personalities
(John Wiley and Sons, 2018) Ağıl, U.; Güdükbay, Uğur
Predicting interest points of virtual characters and accurately simulating their gaze behavior play a significant role for realistic crowd simulations. We propose a saliency model that enables virtual agents to produce plausible gaze behavior. The model measures the effects of distinct saliency features implemented by examining the state-of-the-art perception studies. When predicting an agent's interest point, we compute the saliency scores by using a weighted sum function for other agents and environment objects in the field of view of the agent for each frame. Then, we determine the most salient entity for each agent in the scene; thus, agents gain a visual understanding of their environment. Besides, our model introduces new aspects to crowd perception, such as perceiving characters as groups of people and applying social norms on crowd gaze behavior, effects of agent personality on gaze, gaze copy phenomena, and effects of agent velocity on attention. For evaluation, we compare the resulting saliency gaze model with real-world crowd behavior in captured videos. In the experiments, we simulate the gaze behavior in real crowds. The results show that the proposed approach generates plausible gaze behaviors and is easily adaptable to varying scenarios for virtual crowds.
Open Access
How the ocean personality model affects the perception of crowds
(Institute of Electrical and Electronics Engineers, 2011) Durupınar, F.; Pelechano, N.; Allbeck, J. M.; Güdükbay, Uğur; Badler, N. I.
A personality model named High-Density Autonomous Crowds (HiDAC) simulation system provides individual differences by assigning each person different psychological and physiological traits. Users normally set these parameters to model a crowd's nonuniformity and diversity. The approach creates plausible variations in the crowd and enables novice users to dictate these variations by combining a standard personality model with a high-density crowd simulation. HiDAC addresses the simulation of local behaviors and the global wayfinding of crowds in a dynamically changing environment. It directs autonomous agents' behavior by combining geometric and psychological rules. HiDAC handles collisions through avoidance and response forces. Over long distances, the system applies collision avoidance so that agents can steer around obstacles. HiDAC assigns people specific behaviors. The number of actions they complete depends on their curiosity.
Open Access
Learning from real-life experiences: a data-driven emotion contagion approach towards realistic virtual crowds
(2017-09) Başak, Ahmet Eren
We propose a data-driven approach for tuning, validating and optimizing crowd simulations by learning parameters from real-life videos. We discuss the common traits of incidents and their video footages suitable for the learning step. We then demonstrate the learning process in three real-life incidents: a bombing attack, a panic in subway and a Black Friday rush. We reanimate the incidents using an existing emotion contagion and crowd simulation framework and optimize the parameters that characterize agent behavior with respect to the data extracted from the video footages of the incidents.
Open Access
Modeling and populating virtual cities: automatic production of building models and emergency crowd simulation
(2008) Oğuz, Oğuzcan
In this thesis, we present an automatic building generation method based on procedural modeling approach, and a crowd animation system that simulates a crowd of pedestrians inside a city. While modeling the buildings, to achieve complex and consistent geometries we use shape grammars. The derivation process incorporates randomness so the produced models have the desired variation. The end shapes of the building models could be defined in a certain extent by the derivation rules. The behavior of human crowds inside a city is affected by the simulation scenario. In this thesis, we specifically intend to simulate the virtual crowds in emergency situations caused by an incident, such as a fire, an explosion, or a terrorist attack. We prefer to use a continuum dynamics-based approach to simulate the escaping crowd, which produces more efficient simulations than the agent-based approaches. Only the close proximity of the incident region, which includes the crowd affected by the incident, is simulated. In order to speed up the animation and visualization of the resulting simulation, we employ an offline occlusion culling technique. During runtime, we animate and render a pedestrian model only if it is visible to the user. In the pre-processing stage, the navigable area of the scene is decomposed into a grid of cells and the from-region visibility of these cells is computed with the help of hardware occlusion queries.
Open Access
Psychological parameters for crowd simulation: from audiences to mobs
(Institute of Electrical and Electronics Engineers, 2016) Durupınar, F.; Güdükbay, Uğur; Aman, A.; Badler, N. I.
In the social psychology literature, crowds are classified as audiences and mobs. Audiences are passive crowds, whereas mobs are active crowds with emotional, irrational and seemingly homogeneous behavior. In this study, we aim to create a system that enables the specification of different crowd types ranging from audiences to mobs. In order to achieve this goal we parametrize the common properties of mobs to create collective misbehavior. Because mobs are characterized by emotionality, we describe a framework that associates psychological components with individual agents comprising a crowd and yields emergent behaviors in the crowd as a whole. To explore the effectiveness of our framework we demonstrate two scenarios simulating the behavior of distinct mob types.
Open Access
Realistic modeling of spectator behavior for soccer videogames with CUDA
(2011) Ylmaz, E.; Molla, E.; Yıldız, C.; İşler V.
Soccer has always been one of the most popular videogame genres. When designing a soccer game, designers tend to focus on the game field and game play due to the limited computational resources, and thus the modelling of virtual spectators is paid less attention. In this study we present a novel approach to the modeling of spectator behavior, which treats each spectator as a unique individual. We also propose an independent software layer for sport-based games that simply obtains the game status from the game engine via a simple messaging protocol and computes the spectator behavior accordingly. The result is returned to the game engine, to be used in the animation and rendering of the spectators. Additionally, we offer a customizable spectator knowledge base with well structured XML to minimize coding efforts, while generating individualized behavior. The employed AI is based on fuzzy inference. In order to overcome additional demand for computing realistic spectator behavior, we use GPU parallel computing with CUDA. © 2011 Elsevier Ltd. All rights reserved.
Open Access
Simulating gaze behavior of virtual crowds by predicting interest points
(2016-07) Ağıl, Umut
Creating realistic crowd behavior is one of the major goals in crowd simulations. Simulating gaze behavior and predicting interest points of virtual characters play a signifficant role in creating believable scenes, however this aspect has not received much attention in the field. This study proposes a saliency model, which enables virtual agents to produce gaze behavior. The model measures the effects of distinct pre-deffined saliency features that are implemented by examining the state-of-the-art perception studies. When predicting an agent's interest point, we compute the saliency scores by using a weighted sum function for other agents and environment objects in the field of view of the agent for each frame. Then we determine the most salient entity in the virtual scene according to the viewer agent by comparing the scores. We execute this process for each agent in the scene, thus agents gain a visual understanding about their environment. Besides, our model introduces new aspects to crowd perception, such as perceiving characters as groups of people, gaze copy phenomena and effects of agent velocity on attention. For evaluation, we compare the resulting saliency gaze model with real world crowd behavior in captured videos. In the experiments, we simulate the gaze behavior in real crowds. The results show that the proposed approach generates plausible gaze behaviors and is easily adaptable to varying scenarios for virtual crowds.
Open Access
Using real life incidents for creating realistic virtual crowds with data-driven emotion contagion
(Pergamon Press, 2018) Başak, Ahmet Eren; Güdükbay, Uğur; Durupınar, F.
We propose a data-driven approach for tuning, validating and optimizing crowd simulations by learning parameters from real-life videos. We discuss the common traits of incidents and their video footages suitable for the learning step. We then demonstrate the learning process in three real-life incidents: a bombing attack, a panic situation on the subway and a Black Friday rush. We reanimate the incidents using an existing emotion contagion and crowd simulation framework and optimize the parameters that characterize agent behavior with respect to the data extracted from the video footages of the incidents.
Open Access
Visualization of crowd synchronization on footbridges
(Springer, 2010) Durupınar, F.; Güdükbay, Uğur
This paper proposes a framework for the visualization of crowd walking synchronization on footbridges. The bridge is modeled as a mass-spring system, which is a weakly damped and driven harmonic oscillator. Both the bridge and the pedestrians walking on the bridge are affected by the movement of each other. The crowd acts according to local behavioral rules. Each pedestrian is provided with a kinematic walking system. We extend a current mathematical model of crowd synchronization on footbridges to include human walking model and crowd simulation techniques. We run experiments to evaluate the influence of these extensions on synchronization. © The Visualization Society of Japan 2009.