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Face Recognition Based on Viola-Jones Face Detection Method and Principle Component Analysis (PCA)

Face Recognition Based on Viola-Jones Face Detection Method and Principle Component Analysis (PCA)

Abstract

Face recognition is one of the most important research fields of the last two decades. This is due to the actual use of this technology in automatic detection and monitoring systems. Face attribute and features recognition from images is still a challenge. In this paper, face image recognition is proposed upon local face image rather than focusing on the whole image recognition by applying preprocessing techniques and Viola-Jones method. Principal Component Analysis (PCA) method is used in order to extract the needed features. Experiments show satisfied and more accurate results achieved by the proposed system comparing to the existing systems.

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    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
gold