Principal component analysis for human gait recognition system
This paper represents a method for Human Recognition system using Principal Component Analysis. Human Gait recognition works on the gait of walking subjects to identify people without them knowing or without their permission. The initial step in this kind of system is to generate silhouette fram...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English English |
| Published: |
Institute of Advanced Engineering and Science.
2019
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/72092/ http://irep.iium.edu.my/72092/ http://irep.iium.edu.my/72092/ http://irep.iium.edu.my/72092/1/72092_Principal%20component%20analysis%20for%20human.pdf http://irep.iium.edu.my/72092/7/72092_Principal%20component%20analysis%20for%20human%20gait%20recognition%20system_Scopus.pdf |
| Summary: | This paper represents a method for Human Recognition system using
Principal Component Analysis. Human Gait recognition works on the gait of
walking subjects to identify people without them knowing or without their
permission. The initial step in this kind of system is to generate silhouette
frames of walking human. A number of features couldb be exytacted from
these frames such as centriod ratio, heifht, width and orientation. The
Principal Component Analysis (PCA) is used for the extracted features to
condense the information and produces the main components that can
represent the gait sequences for each waiking human. In the testing phase,
the generated gait sequences are recognized by using a minimum distance
classifier based on eluclidean distance matched with the one that already
exist in the database used to identify walking subject. |
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