| Project/Area Number |
25350666
|
|---|
| Research Category |
Grant-in-Aid for Scientific Research (C)
|
| Allocation Type | Multi-year Fund |
|---|
| Section | 一般 |
|---|
| Research Field |
Rehabilitation science/Welfare engineering
|
|---|
| Research Institution | Nagoya Institute of Technology |
|---|
Principal Investigator |
Kitamura Tadashi 名古屋工業大学, 工学(系)研究科(研究院), 教授 (60114865)
|
|---|
| Co-Investigator(Kenkyū-buntansha) |
SAKO Shinji 名古屋工業大学, 大学院工学研究科, 助教 (30396791)
|
|---|
| Project Period (FY) |
2013-04-01 – 2016-03-31
|
| Project Status |
Completed (Fiscal Year 2015)
|
| Budget Amount *help |
¥4,810,000 (Direct Cost: ¥3,700,000、Indirect Cost: ¥1,110,000)
Fiscal Year 2015: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2014: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
Fiscal Year 2013: ¥2,340,000 (Direct Cost: ¥1,800,000、Indirect Cost: ¥540,000)
|
|---|
| Keywords | 手話認識 / 手指動作 / 非手指動作 / Kinect / Kinect v2 / 手話辞書 / 実時間手話認識 / 深度センサ |
|---|
| Outline of Final Research Achievements |
A sign language consists of manual signals and non-manual signals. Manual signals convey the meaning of the word by three elements, e.g. the shapes, the movements and the positions of the hands. Non-manual signals such as facial expressions, head tilting etc. work to add grammatical functions.
We carried out recognition experiments for manual signals using database recorded by 2 persons, 223 words, twice. The results have shown that the recognition accuracies for 24 hand shapes, 8 positions, 40 movements, are 28.5%, 78.3%, 60.0% respectively. The word recognition accuracy rate was 33.8% using combination of weighted scores of each element. The recognition accuracy rate for top 10 was 79.7%. The recognition experiment of non-manual signals for 3 different motions of head tilting was performed. In the experiments 66 sentences were used for training the Hidden Markov Models of the motions. The recognition rate was 79% for 125 test sentences.
|
