Producing crowd simulations is a time-consuming task. The amount of technical work required for control ling relevant crowd parameters is a hurdle for effective production. In this paper we propose a new authoring method that can easily create crowd simulations with intuitive painting interface. For this, Self Organized Distribution Map (SODM), Stroke-based Flow Field and Gradient Vector Flow (...

Crowd dynamics has been investigated for several years by many researchers. Computer based models prove to offer the optimum way to simulate the crowd dynamics especially in situations that need simulation of realistic behaviour such as in the emergency situations. In this paper, an individual-based model to simulate the behaviour of human crowd is developed. Using the artificial potential fiel...

Crowdsourcing is an emerging area and has evolved as a powerful practice to leverage the collective intelligence of the crowd. It has been applied in various domains ranging from creative resolution of a problem to improving the business process using several platforms such as CrowdFlower, Freelancer and Amazon Mechanical Turk. Crowd is a creative workforce that has niche abilities to solve com...

Crowd work has emerged as a new form of digital gainful employment whose nature is still a black box. In this paper, we focus on the crowd workers – a perspective that has been largely neglected by research. We report results from crowd worker interviews on two different platforms. Our findings illustrate that crowd aggregators as new players restructure the nature of crowd work sustainably wit...

This paper evaluates an automatic technique for detection of abnormal events in crowds. Crowd behaviour is difficult to predict and might not be easily semantically translated. Moreover it is difficult to track individuals in the crowd using state of the art tracking algorithms. Therefore we characterise crowd behaviour by observing the crowd optical flow and use unsupervised feature extraction...

This paper presents a novel approach to learning a dictionary of crowd prototypes for dynamic visual scenes. Recent work in cognitive psychology suggests that crowd perception may be based on pre-attentive ensemble coding mechanisms [24] in the spirit of feedforward hierarchical models of visual processing [4]. We extend a biological model of motion processing [10] with a new dictionary learnin...

The prediction of crowd noise is a problem faced by acoustic consultants. Although consultants are frequently required to predict noise emissions from activities involving crowds of people, there are no prediction methodologies available. This paper discusses the factors influencing crowd noise with the aim of encouraging discussion about how the problem of predicting crowd noise can be overcom...

In this study, we investigate the problem of aggregating crowd opinions for decision making. The Wisdom of Crowds (WoC) theory explains how crowd opinions should be aggregated in order to improve the performance of decision making. Crowd independence and a weighting mechanism are two important factors to crowd wisdom. However, most existing crowd opinion aggregation methods fail to build a diff...

Crowd algorithms often assume workers are inexperienced and thus fail to adapt as workers in the crowd learn a task. These assumptions fundamentally limit the types of tasks that systems based on such algorithms can handle. This paper explores how the crowd learns and remembers over time in the context of human computation, and how more realistic assumptions of worker experience may be used whe...

Crowd animation is a topic of high interest which offers many challenges. One of the most important is the trade-off between rich, realistic behaviors and computational costs. To this end, much effort has been put into creating variety in character representation and animation. Nevertheless, one aspect still lacking realism in virtual crowd characters resides in their attention behaviors. In th...