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 t...

The wisdom of the crowd technique has been shown to be very effective in producing judgments more accurate than those of individuals. However, its performance in situations in which the intended estimates would involve responses of greatly differing magnitudes is less well understood. We first carried out an experiment to elicit people’s estimates in one such domain, populations of U.S. metropo...

The goal of this work is to use computer vision to measure crowd density in outdoor scenes. Crowd density estimation is an important task in crowd monitoring. The assessment is carried out using images of a graduation scene which illustrated variation of illumination due to textured brick surface, clothing and changes of weather. Image features were extracted using Grey Level Dependency Matrix,...

– Group structure is an important characteristic of social crowd. However, up to now, the effect of group structure to crowd behavior has not been widely studied. This is partially due to the fact that modeling group-related behavior is a challenging task because of the many factors that need to be considered. This paper presents a uniformed framework for modeling different group structures in ...

Crowd motion in surveillance videos is comparable to heat motion of basic particles. Inspired by that, we introduce Boltzmann Entropy to measure crowd motion in optical flow field so as to detect abnormal collective behaviors. As a result, the collective crowd moving pattern can be represented as a time series. We found that when most people behave anomaly, the entropy value will increase drast...

The crowd can provide a tremendous amount of data to help us understand the world around us. Data from social network sites, such as Twitter, allow us to implicitly mine data from the crowd, for example to understand different opinions on political issues, the important moments in an event, or the sentiment around particular brands. Other systems, such as CreekWatch, ask members of the crowd to...

The paper describes a Multi-Agent approach to crowd modeling and simulation. After a brief introduction of the Situated Cellular Agents model, the guidelines to the crowd modeling approach is introduced as a way to support the communication among the different actors that are part of the simulation project team. The approach is then applied to describe a complex scenario providing a blend of co...

Using 17420 predictions that we collected from 2037 students, we build on previous research to understand the conditions within which the Wisdom of the Crowd (WoC) improves or worsens as a result of showing individuals the predictions of their peers. We use social learning weights to filter individuals who are better at learning from the crowd to improve accuracy. We also find the novel effect ...

In this paper, we present a data-driven method for crowd simulation with holonification model. With this extra module, the accuracy of simulation will increase and it generates more realistic behaviors of agents. First, we show how to use the concept of holon in crowd simulation and how effective it is. For this reason, we use simple rules for holonification. Using real-world data, we model the...

ABSTRACT: To prevent crowd accidents in large-scale facilities that are available to the general public, it is important to share information on safety measures among organizers, the police, the fire department, and government officials. In this study, we present a crowd simulation system that is capable of sharing visual information on the estimated flow of the crowd and that can be used when ...