Vision-based detection and tracking of moving target in video surveillance
In this paper a real-time detection and tracking of moving targets is presented. The scheme involved four phases. Phase one: Object segmentation which used to identify the foreground objects from the background by using background subtraction based on temporal differencing and a rolling-avera...
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| Main Authors: | , |
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| Format: | Conference or Workshop Item |
| Language: | English English |
| Published: |
2014
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/39040/1/39040.pdf http://irep.iium.edu.my/39040/4/39040_Vision-based%20detection%20and%20tracking%20of%20moving%20target%20in%20video%20surveillance_Scopus.pdf http://irep.iium.edu.my/39040/ http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7031589&tag=1 |
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| Summary: | In this paper a real-time detection and tracking of
moving targets is presented. The scheme involved four phases.
Phase one: Object segmentation which used to identify the
foreground objects from the background by using background
subtraction based on temporal differencing and a rolling-average
background model. Phase two: Object recognition used to
identify the foreground objects that should be tracked by using
simple blob detection. Phase three: Object representation which
takes the outcome from phase two. It computes the
representation of each recognized object to be tracked. Phase 4:
Object tracking that used Kalman filter. The results show that
the tracking system is capable of target shape recovery and
therefore it can successfully track targets with varying distance
from camera or while the camera is zooming |
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