Learning Siamese Features for Finger Spelling Recognition
This paper is devoted to finger spelling recognition on the basis of images acquired by a single color camera. The recognition is realized on the basis of learned low-dimensional embeddings. The embeddings are calculated both by single as well as multiple siamese-based convolutional neural networks....
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| Published in | Advanced Concepts for Intelligent Vision Systems Vol. 10617; pp. 225 - 236 |
|---|---|
| Main Authors | , |
| Format | Book Chapter |
| Language | English |
| Published |
Switzerland
Springer International Publishing AG
2017
Springer International Publishing |
| Series | Lecture Notes in Computer Science |
| Subjects | |
| Online Access | Get full text |
| ISBN | 3319703528 9783319703527 |
| ISSN | 0302-9743 1611-3349 |
| DOI | 10.1007/978-3-319-70353-4_20 |
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| Abstract | This paper is devoted to finger spelling recognition on the basis of images acquired by a single color camera. The recognition is realized on the basis of learned low-dimensional embeddings. The embeddings are calculated both by single as well as multiple siamese-based convolutional neural networks. We train classifiers operating on such features as well as convolutional neural networks operating on raw images. The evaluations are performed on freely available dataset with finger spellings of Japanese Sign Language. The best results are achieved by a classifier trained on concatenated features of multiple siamese networks. |
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| AbstractList | This paper is devoted to finger spelling recognition on the basis of images acquired by a single color camera. The recognition is realized on the basis of learned low-dimensional embeddings. The embeddings are calculated both by single as well as multiple siamese-based convolutional neural networks. We train classifiers operating on such features as well as convolutional neural networks operating on raw images. The evaluations are performed on freely available dataset with finger spellings of Japanese Sign Language. The best results are achieved by a classifier trained on concatenated features of multiple siamese networks. |
| Author | Sako, Shinji Kwolek, Bogdan |
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| Copyright | Springer International Publishing AG 2017 |
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| DOI | 10.1007/978-3-319-70353-4_20 |
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| EISBN | 3319703536 9783319703534 |
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| Editor | Scheunders, Paul Penne, Rudi Popescu, Dan Philips, Wilfried Blanc-Talon, Jacques |
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| PublicationTitle | Advanced Concepts for Intelligent Vision Systems |
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| RelatedPersons | Kleinberg, Jon M. Mattern, Friedemann Naor, Moni Mitchell, John C. Terzopoulos, Demetri Steffen, Bernhard Pandu Rangan, C. Kanade, Takeo Kittler, Josef Weikum, Gerhard Hutchison, David Tygar, Doug |
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| Snippet | This paper is devoted to finger spelling recognition on the basis of images acquired by a single color camera. The recognition is realized on the basis of... |
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| SubjectTerms | CNNs Finger spelling recognition Siamese neural networks |
| Title | Learning Siamese Features for Finger Spelling Recognition |
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