Crowd-labeling emerged from the need to label large-scale and complex data, a tedious, expensive, and time-consuming task. But the problem of obtaining good quality labels from a crowd and their integration is still unresolved. To address this challenge, we propose a new framework that automatically combines and boosts bulk crowd labels supported by limited number of “ground truth” labels from ...

We present a framework for video-driven crowd synthesis. Motion vectors extracted from input crowd video are processed to compute global motion paths. These paths encode the dominant motions observed in the input video. These paths are then fed into a behavior-based crowd simulation framework, which is responsible for synthesizing crowd animations that respect the motion patterns observed in th...

Recent advances in information technologies such as Web 2.0 have dramatically expanded the use of crowd wisdom in dealing with a wide range of problems. Prior research confirms the importance of crowd wisdom in the context of stock markets, but fails to investigate the impact of crowd characteristics on crowd performance. We study the influence of opinion diversity and participant independence ...

The problem of automated crowd segmentation and counting has garnered significant interest in the field of video surveillance. This paper proposes a novel scene invariant crowd segmentation and counting algorithm designed with high accuracy yet low computational complexity in mind, which is key for widespread industrial adoption. A novel low-complexity, scale-normalized feature called Histogram...

Recent advances in crowd simulation models attempt to recreate realistic human behaviour by introducing psychological phenomena in virtual agents. In this direction, psychology studies on personality traits, emotions and emotional contagion attempt to cope with emerging behaviours such as panic spreading and fight picking. This work depicts a way to introduce a model of emotional contagion in t...

Crowd modeling and simulation is an important and active research field, with a wide range of applications such as computer games, military training and evacuation modeling. One important issue in crowd modeling is model calibration through parameter tuning, so as to produce desired crowd behaviors. Common methods such as trial-and-error are time consuming and tedious. This paper proposes an ev...

Crowd analysis becomes the most active-oriented research and trendy topic in computer vision nowadays. Typically, crowd is a unique group of individual or something involves community or society where the phenomena of the crowd are very familiar in a variety of research discipline such as sociology, civil and physics [1]. Within the crowd, there exist many behavior anomalies or abnormality. The...