Analysis-by-synthesis: Pedestrian tracking with crowd simulation models in a multi-camera video network

For tracking systems consisting of multiple cameras with overlapping field-of-views, homography-based approaches are widely adopted to significantly reduce occlusions among pedestrians by sharing information among multiple views. However, in these approaches, the usage of information under real-world coordinates is only at a preliminary level. Therefore, in this paper, a multi-camera tracking system with integrated crowd simulation is proposed in order to explore the possibility to make homography information more helpful. Two crowd simulators with different simulation strategies are used to investigate the influence of the simulation strategy on the final tracking performance. The performance is evaluated by multiple object tracking precision and accuracy (MOTP and MOTA) metrics, for all the camera views and the results obtained under real-world coordinates. The experimental results demonstrate that crowd simulators boost the tracking performance significantly, especially for crowded scenes with higher density. In addition, a more realistic simulation strategy helps to further improve the overall tracking result

Minimal time problem for discrete crowd models with a localized vector field

In this work, we study the minimal time to steer a given crowd to a desired configuration. The control is a vector field, representing a perturbation of the crowd velocity, localized on a fixed control set. We characterize the minimal time for a discrete crowd model, both for exact and approximate controllability. This leads to an algorithm that computes the control and the minimal time. We finally present a numerical simulation

Crowd Simulation

Spousta věcí v přírodě je stejně působivých jako zvířata, která se mohou organizovat do větších a logicky orientovaných seskupení. Tím že dokážeme simulovat toto chování, můžeme vytvořit reálnou podobu davu. Reálné využití pak najdeme v konkrétních oborech lidské činnosti: návrhy veřejných budov, filmové projekty či programování PC her. Tato práce se zaměřuje na popis boidova algoritmu, který je dnes nejpoužívanější co se simulace davu týče.Many things in nature are impressive like animals which can be organized into larger and logical oriented grouping. In that case when we can simulate this behavior than we can create real form of the crowd. Real use can be found in things like: creating public buildings, movie projects or developing games. This thesis focuses on the description of boid's algorithm which is the most used crowd simulation principle today.460 - Katedra informatikyvelmi dobř

Collision detection: review of methods and recent advances in crowd simulation

Crowd simulation is a large complex system that visualizes the behavior of crowd entities' movement and their interactions with the virtual environment. Crowd model is usually integrated into a virtual environment to make the environment alive. In the context of agent-based simulation (as in crowd simulation), it encompasses collision checking between moving agents that are present in the same environment. Hence, it is important to design an efficient and yet effective collision detection in crowd simulation. This is to ensure that it is cost effective toward computational processing usage and still produce a believable behavior. This paper presents a study of collision detection techniques in crowd models, and recent advancement to accelerate the process so that in turn, these efforts could also improve the performance and outcome of crowd model in virtual environment applications

System Issues in Multi-agent Simulation of Large Crowds

Crowd simulation is a complex and challenging domain. Crowds demonstrate many complex behaviours and are consequently difficult to model for realistic simulation systems. Analyzing crowd dynamics has been an active area of research and efforts have been made to develop models to explain crowd behaviour. In this paper we describe an agent based simulation of crowds, based on a continuous field force model. Our simulation can handle movement of crowds over complex terrains and we have been able to simulate scenarios like clogging of exits during emergency evacuation situations. The focus of this paper, however, is on the scalability issues for such a multi-agent based crowd simulation system. We believe that scalability is an important criterion for rescue simulation systems. To realistically model a disaster scenario for a large city, the system should ideally scale up to accommodate hundreds of thousands of agents. We discuss the attempts made so far to meet this challenge, and try to identify the architectural and system constraints that limit scalability. Thereafter we propose a novel technique which could be used to richly simulate huge crowds

Overview of crowd simulation in computer graphics

High-powered technology use computer graphics in education, entertainment, games, simulation, and virtual heritage applications has led it to become an important area of research. In simulation, according to Tecchia et al. (2002), it is important to create an interactive, complex, and realistic virtual world so that the user can have an immersive experience during navigation through the world. As the size and complexity of the environments in the virtual world increased, it becomes more necessary to populate them with peoples, and this is the reason why rendering the crowd in real-time is very crucial. Generally, crowd simulation consists of three important areas. They are realism of behavioral (Thompson and Marchant 1995), high-quality visualization (Dobbyn et al. 2005) and convergence of both areas. Realism of behavioral is mainly used for simple 2D visualizations because most of the attentions are concentrated on simulating the behaviors of the group. High quality visualization is regularly used for movie productions and computer games. It gives intention on producing more convincing visual rather than realism of behaviors. The convergences of both areas are mainly used for application like training systems. In order to make the training system more effective, the element of valid replication of the behaviors and high-quality visualization is added