Abstract:
The growth of technology continues to make both
hardware and software affordable and accessible creating space
for the emergence of new applications. Rapid growth in computer
vision and image processing applications have been evident in
recent years. One area of interest in vision and image processing
is automated identification of objects in real-time or recorded
video streams and analysis of these identified objects. An important
topic of research in this context is identification of humans
and interpreting their actions. Human motion identification and
video processing have been used in critical crime investigations
and highly technical applications usually involving skilled human
experts. Although the technology has many uses that can be
applied in every day activities, it has not been put into such
use due to requirements in sophisticated technology, human skill
and high implementation costs. This paper presents a system,
which is a major part of a project called movelt (movements
interpreted), that receives video as input to process and recognize
gestures of the objects of interest (the human whole body). Basic
functionality of this system is to receive video stream as input and
produce outputs gesture analysis of each object through a staged
process of object detection, tracking, modelling and recognition
of gestures as intermediate steps.
