Accurate eye detection using generalized binary pattern | IEEE Conference Publication | IEEE Xplore

Accurate eye detection using generalized binary pattern


Abstract:

This paper proposes the eye detection using generalized binary pattern (GBP). The GBP can generate all possible patterns of ordered comparisons within a 3 × 3 neighborhoo...Show More

Abstract:

This paper proposes the eye detection using generalized binary pattern (GBP). The GBP can generate all possible patterns of ordered comparisons within a 3 × 3 neighborhood. Since existing local structure patterns consider all neighboring pixels around a given pixel, the number of possible patterns is fixed and limited to 2n. However, since the GBP takes the ordered comparisons of some partial neighboring pixels around a given pixel, a total of 502 different types can be generated in 3 × 3 block. So, our proposed GBP generates 19,162 binary patterns at the given pixel. Among the possible binary patterns, we take an effective set of pattern and position by the AdaBoost feature selection algorithm. Experimental results shows that the GBP provides higher eye detection accuracy on the BioID and FERET databases than other existing local structure patterns such as LBP and MCT.
Published in: 2013 IEEE RO-MAN
Date of Conference: 26-29 August 2013
Date Added to IEEE Xplore: 15 October 2013
Electronic ISBN:978-1-4799-0509-6

ISSN Information:

Conference Location: Gyeongju, Korea (South)

References

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