Human identification system based on moment invariant features
Video surveillance is an active research topic in computer vision. Recent research in video surveillance system has shown an increasing focus on creating reliable systems utilizing non-computationally expensive technique for detecting and observing humans’ appearance, movements and activities. I...
| Main Authors: | , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2012
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/27221/ http://irep.iium.edu.my/27221/ http://irep.iium.edu.my/27221/1/06271183.pdf |
| Summary: | Video surveillance is an active research topic in
computer vision. Recent research in video surveillance system
has shown an increasing focus on creating reliable systems
utilizing non-computationally expensive technique for detecting
and observing humans’ appearance, movements and activities. In
this paper, we present a human identification technique suitable
for video surveillance. The technique we propose includes
background subtraction, foreground segmentation, feature
extraction and classification. First of all, we extract all
foreground objects from the background. Then, we perform a
morphological reconstruction algorithm to recover the distorted
foreground objects. The feature extraction is done using affine
moment invariants of full body and head-shoulder of the
extracted foreground objects and these were used to identify
human. When the partial occlusion occurs, although feature of
full body cannot be extracted, still the features of head shoulder
can be extracted. Thus, it has a better classification on solving the
issue of the loss of property arising from human occluded easily
in practical applications. The experiment results show that this
method is effective, and it has strong robustness. |
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