Attire-based photo annotation

Many commercial and free photo organizers allow users to manage their personal photo collections by grouping them into folder, album and by dates. However, these are done manually by dragging and dropping these photos into named albums and star-marked folders. In this paper, we proposed automated ph...

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Published in:IC3e 2014 - 2014 IEEE Conference on e-Learning, e-Management and e-Services
Main Author: Jamil N.; Sa'dan S.A.; Narawi A.; Gobil A.R.
Format: Conference paper
Language:English
Published: Institute of Electrical and Electronics Engineers Inc. 2014
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-84928752828&doi=10.1109%2fIC3e.2014.7081257&partnerID=40&md5=885c5bccaea071fd6bf97e6525118ed8
id 2-s2.0-84928752828
spelling 2-s2.0-84928752828
Jamil N.; Sa'dan S.A.; Narawi A.; Gobil A.R.
Attire-based photo annotation
2014
IC3e 2014 - 2014 IEEE Conference on e-Learning, e-Management and e-Services


10.1109/IC3e.2014.7081257
https://www.scopus.com/inward/record.uri?eid=2-s2.0-84928752828&doi=10.1109%2fIC3e.2014.7081257&partnerID=40&md5=885c5bccaea071fd6bf97e6525118ed8
Many commercial and free photo organizers allow users to manage their personal photo collections by grouping them into folder, album and by dates. However, these are done manually by dragging and dropping these photos into named albums and star-marked folders. In this paper, we proposed automated photo organization by labeling who are in the images as well as group them into events accordingly. This process is known as automated photo annotation. In most automated photo annotation, basic metadata such as time and date are typically used to group them by events. We took one step further by incorporating the clothing colour feature to perform automated photo annotation. A total of 175 photographs comprising 138 frontal faces are selected from events such as Eid celebration, birthday celebration and outdoor occasions. The face features are described using eigenfaces, while the clothing colours are represented using La∗b∗ colour histogram. Julian date format is added into the feature vector and three metric-distance similarity measures are compared for performance. Our experiment showed that the highest person annotation rate was achieved by combination of face and clothing feature at 82.5 percent. On the other hand, event is best annotated using combination of face and time features. © 2014 IEEE.
Institute of Electrical and Electronics Engineers Inc.

English
Conference paper

author Jamil N.; Sa'dan S.A.; Narawi A.; Gobil A.R.
spellingShingle Jamil N.; Sa'dan S.A.; Narawi A.; Gobil A.R.
Attire-based photo annotation
author_facet Jamil N.; Sa'dan S.A.; Narawi A.; Gobil A.R.
author_sort Jamil N.; Sa'dan S.A.; Narawi A.; Gobil A.R.
title Attire-based photo annotation
title_short Attire-based photo annotation
title_full Attire-based photo annotation
title_fullStr Attire-based photo annotation
title_full_unstemmed Attire-based photo annotation
title_sort Attire-based photo annotation
publishDate 2014
container_title IC3e 2014 - 2014 IEEE Conference on e-Learning, e-Management and e-Services
container_volume
container_issue
doi_str_mv 10.1109/IC3e.2014.7081257
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-84928752828&doi=10.1109%2fIC3e.2014.7081257&partnerID=40&md5=885c5bccaea071fd6bf97e6525118ed8
description Many commercial and free photo organizers allow users to manage their personal photo collections by grouping them into folder, album and by dates. However, these are done manually by dragging and dropping these photos into named albums and star-marked folders. In this paper, we proposed automated photo organization by labeling who are in the images as well as group them into events accordingly. This process is known as automated photo annotation. In most automated photo annotation, basic metadata such as time and date are typically used to group them by events. We took one step further by incorporating the clothing colour feature to perform automated photo annotation. A total of 175 photographs comprising 138 frontal faces are selected from events such as Eid celebration, birthday celebration and outdoor occasions. The face features are described using eigenfaces, while the clothing colours are represented using La∗b∗ colour histogram. Julian date format is added into the feature vector and three metric-distance similarity measures are compared for performance. Our experiment showed that the highest person annotation rate was achieved by combination of face and clothing feature at 82.5 percent. On the other hand, event is best annotated using combination of face and time features. © 2014 IEEE.
publisher Institute of Electrical and Electronics Engineers Inc.
issn
language English
format Conference paper
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record_format scopus
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