| Summary: | Person Re-Identification is a process where the
algorithm in charge of matching the similarity of two objects .
This method can be used as an alternative solution for the current
traditional security surveillance . Many modern technologies
that use this model, especially in the use of Video Surveillance .
The expected output from the use of this model is the process of
monitoring and detecting the similarity of two human objects
more efficiently and accurately . However , in its implementation
there are still many problems found by previous researchers
related to Person Identification . Some of the problems that are
often encountered in re-identification are image occlusion , pose
variance , illuminati , etc. One of the problems that occur is the
difference in poses , the difference in poses causes the re -
identification process to often experience errors because the
features obtained by the two images may experience differences .
In this study , trying to implement the algorithm on a video
dataset . There is an additional preprocessing which uses the
image segmentation method to extract objects from the video
dataset . After pre -processing , the image obtained will be reidentified
using the Siamese Network Algorithm. The test results
obtained an accuracy of 51% and 54% for each architecture .
While the accuracy value of object detection obtained is 0.359
and 0.378 , which means that the addition of segmentation
using the background subtraction model when
compared to
previous studies is still not effective in dealing with the problem of
different poses
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