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Long distance face recognition for enhanced performance of internet of things service interface
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| Zeitschriftentitel: | Computer Science and Information Systems |
|---|---|
| Personen und Körperschaften: | , |
| In: | Computer Science and Information Systems, 11, 2014, 3, S. 961-974 |
| Format: | E-Article |
| Sprache: | Englisch |
| veröffentlicht: |
National Library of Serbia
|
| Schlagwörter: |
| author_facet |
Moon, Hae-Min Pan, Sung Moon, Hae-Min Pan, Sung |
|---|---|
| author |
Moon, Hae-Min Pan, Sung |
| spellingShingle |
Moon, Hae-Min Pan, Sung Computer Science and Information Systems Long distance face recognition for enhanced performance of internet of things service interface General Computer Science |
| author_sort |
moon, hae-min |
| spelling |
Moon, Hae-Min Pan, Sung 1820-0214 2406-1018 National Library of Serbia General Computer Science http://dx.doi.org/10.2298/csis130926059m <jats:p>As many objects in the human ambient environment are intellectualized and networked, research on IoT technology have increased to improve the quality of human life. This paper suggests an LDA-based long distance face recognition algorithm to enhance the intelligent IoT interface. While the existing face recognition algorithm uses single distance image as training images, the proposed algorithm uses face images at distance extracted from 1m to 5m as training images. In the proposed LDA-based long distance face recognition algorithm, the bilinear interpolation is used to normalize the size of the face image and a Euclidean Distance measure is used for the similarity measure. As a result, the proposed face recognition algorithm is improved in its performance by 6.1% at short distance and 31.0% at long distance, so it is expected to be applicable for USN?s robot and surveillance security systems.</jats:p> Long distance face recognition for enhanced performance of internet of things service interface Computer Science and Information Systems |
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National Library of Serbia, 2014 |
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National Library of Serbia, 2014 |
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2014 |
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National Library of Serbia |
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Computer Science and Information Systems |
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49 |
| title |
Long distance face recognition for enhanced performance of internet of things service interface |
| title_unstemmed |
Long distance face recognition for enhanced performance of internet of things service interface |
| title_full |
Long distance face recognition for enhanced performance of internet of things service interface |
| title_fullStr |
Long distance face recognition for enhanced performance of internet of things service interface |
| title_full_unstemmed |
Long distance face recognition for enhanced performance of internet of things service interface |
| title_short |
Long distance face recognition for enhanced performance of internet of things service interface |
| title_sort |
long distance face recognition for enhanced performance of internet of things service interface |
| topic |
General Computer Science |
| url |
http://dx.doi.org/10.2298/csis130926059m |
| publishDate |
2014 |
| physical |
961-974 |
| description |
<jats:p>As many objects in the human ambient environment are intellectualized and
networked, research on IoT technology have increased to improve the quality
of human life. This paper suggests an LDA-based long distance face
recognition algorithm to enhance the intelligent IoT interface. While the
existing face recognition algorithm uses single distance image as training
images, the proposed algorithm uses face images at distance extracted from 1m
to 5m as training images. In the proposed LDA-based long distance face
recognition algorithm, the bilinear interpolation is used to normalize the
size of the face image and a Euclidean Distance measure is used for the
similarity measure. As a result, the proposed face recognition algorithm is
improved in its performance by 6.1% at short distance and 31.0% at long
distance, so it is expected to be applicable for USN?s robot and surveillance
security systems.</jats:p> |
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| author | Moon, Hae-Min, Pan, Sung |
| author_facet | Moon, Hae-Min, Pan, Sung, Moon, Hae-Min, Pan, Sung |
| author_sort | moon, hae-min |
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| container_title | Computer Science and Information Systems |
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| description | <jats:p>As many objects in the human ambient environment are intellectualized and networked, research on IoT technology have increased to improve the quality of human life. This paper suggests an LDA-based long distance face recognition algorithm to enhance the intelligent IoT interface. While the existing face recognition algorithm uses single distance image as training images, the proposed algorithm uses face images at distance extracted from 1m to 5m as training images. In the proposed LDA-based long distance face recognition algorithm, the bilinear interpolation is used to normalize the size of the face image and a Euclidean Distance measure is used for the similarity measure. As a result, the proposed face recognition algorithm is improved in its performance by 6.1% at short distance and 31.0% at long distance, so it is expected to be applicable for USN?s robot and surveillance security systems.</jats:p> |
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| imprint | National Library of Serbia, 2014 |
| imprint_str_mv | National Library of Serbia, 2014 |
| institution | DE-Gla1, DE-Zi4, DE-15, DE-Pl11, DE-Rs1, DE-105, DE-14, DE-Ch1, DE-L229, DE-D275, DE-Bn3, DE-Brt1, DE-Zwi2, DE-D161 |
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| series | Computer Science and Information Systems |
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| spelling | Moon, Hae-Min Pan, Sung 1820-0214 2406-1018 National Library of Serbia General Computer Science http://dx.doi.org/10.2298/csis130926059m <jats:p>As many objects in the human ambient environment are intellectualized and networked, research on IoT technology have increased to improve the quality of human life. This paper suggests an LDA-based long distance face recognition algorithm to enhance the intelligent IoT interface. While the existing face recognition algorithm uses single distance image as training images, the proposed algorithm uses face images at distance extracted from 1m to 5m as training images. In the proposed LDA-based long distance face recognition algorithm, the bilinear interpolation is used to normalize the size of the face image and a Euclidean Distance measure is used for the similarity measure. As a result, the proposed face recognition algorithm is improved in its performance by 6.1% at short distance and 31.0% at long distance, so it is expected to be applicable for USN?s robot and surveillance security systems.</jats:p> Long distance face recognition for enhanced performance of internet of things service interface Computer Science and Information Systems |
| spellingShingle | Moon, Hae-Min, Pan, Sung, Computer Science and Information Systems, Long distance face recognition for enhanced performance of internet of things service interface, General Computer Science |
| title | Long distance face recognition for enhanced performance of internet of things service interface |
| title_full | Long distance face recognition for enhanced performance of internet of things service interface |
| title_fullStr | Long distance face recognition for enhanced performance of internet of things service interface |
| title_full_unstemmed | Long distance face recognition for enhanced performance of internet of things service interface |
| title_short | Long distance face recognition for enhanced performance of internet of things service interface |
| title_sort | long distance face recognition for enhanced performance of internet of things service interface |
| title_unstemmed | Long distance face recognition for enhanced performance of internet of things service interface |
| topic | General Computer Science |
| url | http://dx.doi.org/10.2298/csis130926059m |