| Presentation | 2017-05-28 A study on JSL Finger Spelling Recognition Using Convolutional Neural Networks Shinji Sako, Hana Hosoe, Bogdan Kwolek, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | Recently, a few methods for recognition of hand postures on depth maps using convolutional neural networks were proposed. In this paper, we present a framework for recognition of static finger spelling in Japanese Sign Language. The recognition takes place on the basis of single gray image. The finger spelled signs are recognized using a convolutional neural network. A dataset consisting of 5000 samples has been recorded. A 3D articulated hand model has been designed to generate synthetic finger spellings and to extend the real hand gestures. Experimental results demonstrate that owing to sufficient amount of training data a high recognition rate can be attained on images from a single RGB camera. The full dataset and Caffe model are available for download. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | sign language, / finger spelling recognition / convolutional neural networks |
| Paper # | WIT2017-10 |
| Date of Issue | 2017-05-20 (WIT) |
| Conference Information | |
| Committee | WIT / ASJ-H |
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| Conference Date | 2017/5/27(2days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | RION Co., LTD. |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Psychological and Physiological Acoustics and Well-being Information Technology, etc. |
| Chair | Kiyohiko Nunokawa(Tokyo International Univ.) / Hirahara Tatsuya(富山県立大) |
| Vice Chair | Chikamune Wada(Kyushu Inst. of Tech.) / Furukawa Shigeto(NTT) |
| Secretary | Chikamune Wada(Nagoya Inst. of Tech.) / Furukawa Shigeto(AIST) |
| Assistant | Tomohiro Amemiya(NTT) / Takeaki Shionome(Tohoku Bunka Gakuen University) / Manabi Miyagi(Tsukuba Univ. of Tech.) / Takashi Handa(Saitama Industrial Technology Center) |
| Paper Information | |
| Registration To | Technical Committee on Well-being Information Technology / Auditory Research Meeting |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | A study on JSL Finger Spelling Recognition Using Convolutional Neural Networks |
| Sub Title (in English) | |
| Keyword(1) | sign language, |
| Keyword(2) | finger spelling recognition |
| Keyword(3) | convolutional neural networks |
| 1st Author's Name | Shinji Sako |
| 1st Author's Affiliation | Nagoya Institute of Technology(NIT) |
| 2nd Author's Name | Hana Hosoe |
| 2nd Author's Affiliation | Nagoya Institute of Technology(NIT) |
| 3rd Author's Name | Bogdan Kwolek |
| 3rd Author's Affiliation | AGH University of Technology(AGH) |
| Date | 2017-05-28 |
| Paper # | WIT2017-10 |
| Volume (vol) | vol.117 |
| Number (no) | WIT-66 |
| Page | pp.pp.45-49(WIT), |
| #Pages | 5 |
| Date of Issue | 2017-05-20 (WIT) |