Abstract:
Understanding how people exploit nonverbal aspects of their communication to
coordinate their activities and social relationships is a fundamental scientific challenge.
Deeper insights into nonverbal communication can have a profound impact on how
we link theories of perception, learning, cognition and action to models of interactions
and groups at the social level. Models of nonverbal behaviours in interaction are
essential for collaboration tools, human-computer and virtual interaction and other
assistive technologies designed to support people in real-world activities. -
This final year project Analysis of Crowd Behaviour using Face Expressions
(ACBE) presents a study on the analysis of the crowd using computer vision
techniques, covering different aspects such as tracking people and frequent changes of
behaviour of people. Although the crowds are made up of independent, each with their
own goals and behaviours, crowd behaviour is widely understood as having collective
characteristics that can be described in general terms. For example, descriptions like
"an angry", a "peaceful", etc. are accepted. For this purpose an analysis has been done
based on the facial expressions of group(s) in a crowd. The main scope of this project
was to develop an application used for security purpose in crowded places i.e. Railway
station, Airports and School to identify any specious entity around.
On the final outcome our system will tells the current emotions of persons in
group. On the basis of current mood of the persons in a group system will analyse and
detect the current environment. In the end it will predict the next behaviour of a
selected person based on current detected mood and environment.
