The scared cities of Makkah Al Mukarramah and Madina Al Munawarah host millions of pilgrims every year. During Hajj, the movement of large number of people has a unique spatial and temporal constraints, which makes Hajj one of toughest challenges for crowd management. In this paper, we propose a computer vision based framework that automatically analyses video sequence and computes important me...

Crowdsourced testing is an emerging trend in software testing, which relies on crowd workers to accomplish test tasks. Typically, a crowdsourced testing task aims to detect as many bugs as possible within a limited budget. For a specific test task, not all crowd workers are qualified to perform it, and different test tasks require crowd workers to have different experiences, domain knowledge, e...

In this paper, we propose a deep Convolutional Neural Network (CNN) for counting the number of people across a line-of-interest (LOI) in surveillance videos. It is a challenging problem and has many potential applications. Observing the limitations of temporal slices used by state-of-the-art LOI crowd counting methods, our proposed CNN directly estimates the crowd counts with pairs of video fra...

Crowds pose an interesting example of a complex system in which emergent behaviour is observed out of the interaction of many individual agents. This behaviour can be very important in the safe design of sports and other stadia, especially in the case of possible emergency situations. For this reason crowd dynamics is of great interest to architects. The purpose of this project is to review the...

Cloud computing is a highly scalable computing paradigm where resources are delivered to users on demand via Internet. There are several areas that can benefit from cloud computing and one in special is gaining much attention: the flash-crowd handling. Flash-crowd events happen when servers are unable to handle the volume of requests for a specific content (or a set of contents) that actually r...

There are still significant problems in the planning, design and management of public facilities subject to dense pedestrian traffic. The automation of data collection and analysis of crowd behaviour is increasingly desirable in design of facilities and long-term site management using image processing techniques with existing closed-circuit television systems. We have investigated a number of t...

Ubiquitous crowd-sourcing has become a popular mechanism to harvest knowledge from the masses. OpenStreetMap (OSM) is a successful example of ubiquitous crowd-sourcing, where citizens volunteer geographic information in order to build and maintain an accurate map of the changing world. Research has shown that OSM information is accurate, by comparing it with centrally maintained spatial informa...

The creative potential from innovative contributions of the crowd constitutes some critical challenges. The quantity of contributions and the resource demands to identify valuable ideas is high and remains challenging for firms that apply open innovation initiatives. To solve these problems, research on algorithmic approaches proved to be a valuable way by identifying metrics to distinguish bet...

With an increasing micro-labor supply and a larger available workforce, new microtask platforms have emerged providing an extensive list of marketplaces where microtasks are offered by requesters and completed by crowd workers. The current microtask crowdsourcing infrastructure does not offer the possibility to be recognised for already accomplished and offered work in different microtask platf...

There are considerable differences in remuneration and environment between crowd-sourced workers and the traditional laboratory study participant. If crowd-sourced participants are to be used for information retrieval user studies, we need to know if and to what extent their behavior on information retrieval tasks differs from the accepted standard of laboratory participants. With both crowd-so...