A state of the art comparison of databases for facial occlusion
Face recognition continues to be one of the most popular research areas of image processing and computer vision. There are various face databases available to researchers for face detection and recognition. These databases are customized for a particular need of one algorithm. They are...
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my-unisza-ir.69072022-09-13T06:14:15Z http://eprints.unisza.edu.my/6907/ A state of the art comparison of databases for facial occlusion Fatma Susilawati, Mohamad Abdulganiyu, Abdu Yusuf Zahraddeen, Sufyanu QA75 Electronic computers. Computer science Face recognition continues to be one of the most popular research areas of image processing and computer vision. There are various face databases available to researchers for face detection and recognition. These databases are customized for a particular need of one algorithm. They are range in size, scope, and purpose. Few of these databases from the literature contain face occlusions in several positions of the faces to enable real world applications. In this paper, we present four different occlusion face databases. These are Aleix-Robert (AR),Bosphorus, Labeled Faces in the Wild (LFW), and University of Milano Bicocca Database (UMB) face databases. At each section, the key features of the database are presented with the recording conditions, though not all of them are discussed at the same level of details. Detailed comparisons of the databases were made based on controlled and uncontrolled databases, 2D and 3D databases and also their uniqueness. Comparison was also made with other databases out of the categorization mentioned. The databases are useful for performing a rigorous benchmarking of face detection and recognition algorithms. Penerbit UTM Press 2015 Article PeerReviewed image en http://eprints.unisza.edu.my/6907/1/FH02-FIK-15-04636.jpg Fatma Susilawati, Mohamad and Abdulganiyu, Abdu Yusuf and Zahraddeen, Sufyanu (2015) A state of the art comparison of databases for facial occlusion. Jurnal Teknologi, 77 (13). pp. 111-117. ISSN 01279696 |
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QA75 Electronic computers. Computer science Fatma Susilawati, Mohamad Abdulganiyu, Abdu Yusuf Zahraddeen, Sufyanu A state of the art comparison of databases for facial occlusion |
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Face recognition continues to be one of the most popular research areas of image processing and computer vision. There are various face databases available to researchers for face detection and recognition. These databases are customized for a particular need of one algorithm. They are range in size, scope, and purpose. Few of these databases from the literature contain face occlusions in several positions of the faces to enable real world applications. In this paper, we present four different occlusion face databases. These are Aleix-Robert (AR),Bosphorus, Labeled Faces in the Wild (LFW), and University of Milano Bicocca Database (UMB) face databases. At each section, the key features of the database are presented with the recording conditions, though not all of them are discussed at the same level of details. Detailed comparisons of the databases were made based on controlled and uncontrolled databases, 2D and 3D databases and also their uniqueness. Comparison was also made with other databases out of the categorization mentioned. The databases are useful for performing a rigorous benchmarking of face detection and recognition algorithms. |
format |
Article |
author |
Fatma Susilawati, Mohamad Abdulganiyu, Abdu Yusuf Zahraddeen, Sufyanu |
author_facet |
Fatma Susilawati, Mohamad Abdulganiyu, Abdu Yusuf Zahraddeen, Sufyanu |
author_sort |
Fatma Susilawati, Mohamad |
title |
A state of the art comparison of databases for facial occlusion |
title_short |
A state of the art comparison of databases for facial occlusion |
title_full |
A state of the art comparison of databases for facial occlusion |
title_fullStr |
A state of the art comparison of databases for facial occlusion |
title_full_unstemmed |
A state of the art comparison of databases for facial occlusion |
title_sort |
state of the art comparison of databases for facial occlusion |
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Penerbit UTM Press |
publishDate |
2015 |
url |
http://eprints.unisza.edu.my/6907/1/FH02-FIK-15-04636.jpg http://eprints.unisza.edu.my/6907/ |
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