Estimating count and density maps from crowd images has a wide range of applications
such as video surveillance, traffic monitoring, public safety and urban planning. In addition …

This review article surveys extensively the current progresses made toward video-based
human activity recognition. Three aspects for human activity recognition are addressed …

Sensors are devices that quantify the physical aspects of the world around us. This ability is
important to gain knowledge about human activities. Human Activity recognition plays an …

In a crowded public space, people often walk in groups, either with people they know or
strangers. Associating a group of people over space and time can assist understanding …

As an emerging and freely available urban big data, Street View Imagery (SVI) has proven to
be a useful resource to examine various urban phenomena in human behavior, the built …

Interest in automatic crowd behaviour analysis has grown considerably in the last few years.
Crowd behaviour analysis has become an integral part all over the world for ensuring …

In this paper, proximity-based Bluetooth tracking is postulated as an efficient and effective
methodology for analysing the complex spatiotemporal dynamics of visitor movements at …

In this work, we propose an unsupervised approach for crowd scene anomaly detection and
localization using a social network model. Using a window-based approach, a video scene …

In this paper, we propose a novel SpatioTemporal convolutional Dense Network (STDNet) to
address the video-based crowd counting problem, which contains the decomposition of 3D …

Intelligence about the spatio-temporal behaviour of individuals is valuable in many settings.
Generating tracking data is a necessity for this analysis and requires an appropriate …