Ahmed Alostaz and Basil Hamed
FPID, visual object tracking, optimized bootstrap particle ﬁlter, particle swarm optimization (PSO)
This automated object tracking system is very essential in terms of
surveillance system and many more applications. In this paper, the
design of fuzzy proportional-integral-derivative controller is proposed
to control a robot eye to achieve a real-time video object tracking.
The controller uses vision-based object tracking as feedback and
generates velocity commands for the robot eye to keep the object of
interest (OBI) in video at the centre of the image frame. The particle
ﬁlter (PF) is used to track OBI in video by estimating its position in
image frame. A new optimized bootstrap PF (OBPF) is introduced
solving problem of PF on video object tracking for rigid motion.
A new adaptive OBPF (AOBPF) is introduced for tracking object
that has variable speed. The experimental and comparison results of
the designed controllers using diﬀerent methods of optimization are
presented to demonstrate and to verify the proposed video object
tracking system performance.