Support vector machine for classify dynamic human/vehicle shapes.
Currently Support Vector Machines (SVM) became subject of interest because of its ability to give high classification performance in a wide area of application. Most of the classifier model especially based on supervised learning involve complicated learning model and yet the performance sometimes w...
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| Main Authors: | , |
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| Format: | Conference or Workshop Item |
| Published: |
2008
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| Subjects: | |
| Online Access: | http://eprints.uthm.edu.my/2262/ http://eprints.uthm.edu.my/2262/1/Support_vector_machine_for.pdf |
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| Summary: | Currently Support Vector Machines (SVM) became
subject of interest because of its ability to give high
classification performance in a wide area of
application. Most of the classifier model especially
based on supervised learning involve complicated
learning model and yet the performance sometimes
worst. This paper proposes a SVM model to classify
between human and vehicle shapes in various pose.
SVM classify data by first construct a decision surface
that maximizes the margin between the data. For
testing new data, SVM will calculate the sign signifying
where this new data reside in the constructed decision
surface. The developed model will be used to classify
an outdoor scene of human and vehicle shapes in
dynamic pose. Results of the experiments showed a
satisfied performance with the proposed appr |
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