Authors:
Angelo Cardellicchio
1
;
Tiziana D'Orazio
1
;
Tiziano Politi
2
and
Vito Renò
1
Affiliations:
1
National Research Council, Italy
;
2
Politecnico di Bari, Italy
Keyword(s):
Color Analysis, Feature Extraction, Histograms.
Related
Ontology
Subjects/Areas/Topics:
Computer Vision, Visualization and Computer Graphics
;
Features Extraction
;
Image and Video Analysis
;
Motion, Tracking and Stereo Vision
;
Video Surveillance and Event Detection
Abstract:
Person re-identification has increasingly become an interesting task in the computer vision field, especially
after the well known terroristic attacks on the World Trade Center in 2001. Even if video surveillance systems
exist since the early 1950s, the third generation of such systems is a relatively modern topic and refers to
systems formed by multiple fixed or mobile cameras - geographically referenced or not - whose information
have to be handled and processed by an intelligent system. In the last decade, researchers are focusing their
attention on the person re-identification task because computers (and so video surveillance systems) can handle
a huge amount of data reducing the time complexity of the algorithms. Moreover, some well known image
processing techniques - i.e. background subtraction - can be embedded directly on cameras, giving modularity
and flexibility to the whole system. The aim of this work is to present an appearance-based method for person
re-identif
ication that models the chromatic relationship between both different frames and different areas of
the same frame. This approach has been tested against two public benchmark datasets (ViPER and ETHZ) and
the experiments demonstrate that the person re-identification processing by means of intra frame relationships
is robust and shows great results in terms of recognition percentage.
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