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INTELLIGENT VISUAL SURVEILLANCE. Edition No. 1

Description:
In this book, we describe the proposed pedestrian
classification and tracking system that is
able to track and label multiple people in an
outdoor environment such as a railway station. We
propose an approach that combines blob matching with
particle filtering to track multiple people
in the scene, i.e., the proposed method selects the
successful features of blob matching and particle
filtering for tracking. In addition, a
novel appearance model derived from the colour
information from both the moving regions and
theoriginal input colour image is proposed to track
people in the event of poor foreground extraction.
Additionally, the proposed appearance model also
includes spatial information of the human
body in both vertical and horizontal directions,
making location more accurate. Furthermore, a novel
method to extract cars from moving regions including
shadow area, based
on shape and colour information, is proposed.
Chamfer template matching score, and non-shadow
region edge score, are applied as the shape
information; while the shadow confidence score
(SCS) is used as the colour information.
 
Author
Suyu, Kong.
Suyu Kong received his Master of Philosophy degree in compute
science from the University
of Queensland. During his postgraduate period, he received the
scholarship from National ICT, Australia(NICTA) and also worked
there as a reserch student. His papers about people tracking for
visual surveillance have been accepted by AVSS and ICPR.
 
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INTELLIGENT VISUAL SURVEILLANCE. Edition No. 1

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