抄録
We propose a method of tracking 3D position, posture, and shapes of human hands from multiple-viewpoint images. Self-occlusion and hand-hand occlusion are serious problems in the vision-based hand tracking. Our system employs multiple-viewpoint and viewpoint selection mechanism to reduce these problems. Each hand position is tracked with a Kalman filter and the motion vectors are updated with image features in selected images that do not include hand-hand occlusion. 3D hand postures are estimated with a small number of reliable image features. These features are extracted based on distance transformation, and they are robust against changes in hand shape and self-occlusion. Finally, a `best view' image is selected for each hand for shape recognition. The shape recognition process is based on a Fourier descriptor. Our system can be used as a user interface device in a virtual environment, replacing glove-type devices and overcoming most of the disadvantages of contact-type devices.
| 元の言語 | English |
|---|---|
| ホスト出版物のタイトル | Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition |
| 出版者 | IEEE |
| ページ | 473-478 |
| ページ数 | 6 |
| 巻 | 1 |
| 出版物ステータス | Published - 1999 |
| 外部発表 | Yes |
| イベント | Proceedings of the 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'99) - Fort Collins, CO, USA 継続期間: 1999 6 23 → 1999 6 25 |
Other
| Other | Proceedings of the 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'99) |
|---|---|
| 市 | Fort Collins, CO, USA |
| 期間 | 99/6/23 → 99/6/25 |
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ASJC Scopus subject areas
- Computer Vision and Pattern Recognition
- Software
- Control and Systems Engineering
- Electrical and Electronic Engineering
これを引用
Multiple-hand-gesture tracking using multiple cameras. / Utsumi, Akira; Ohya, Jun.
Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 巻 1 IEEE, 1999. p. 473-478.研究成果: Chapter
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TY - CHAP
T1 - Multiple-hand-gesture tracking using multiple cameras
AU - Utsumi, Akira
AU - Ohya, Jun
PY - 1999
Y1 - 1999
N2 - We propose a method of tracking 3D position, posture, and shapes of human hands from multiple-viewpoint images. Self-occlusion and hand-hand occlusion are serious problems in the vision-based hand tracking. Our system employs multiple-viewpoint and viewpoint selection mechanism to reduce these problems. Each hand position is tracked with a Kalman filter and the motion vectors are updated with image features in selected images that do not include hand-hand occlusion. 3D hand postures are estimated with a small number of reliable image features. These features are extracted based on distance transformation, and they are robust against changes in hand shape and self-occlusion. Finally, a `best view' image is selected for each hand for shape recognition. The shape recognition process is based on a Fourier descriptor. Our system can be used as a user interface device in a virtual environment, replacing glove-type devices and overcoming most of the disadvantages of contact-type devices.
AB - We propose a method of tracking 3D position, posture, and shapes of human hands from multiple-viewpoint images. Self-occlusion and hand-hand occlusion are serious problems in the vision-based hand tracking. Our system employs multiple-viewpoint and viewpoint selection mechanism to reduce these problems. Each hand position is tracked with a Kalman filter and the motion vectors are updated with image features in selected images that do not include hand-hand occlusion. 3D hand postures are estimated with a small number of reliable image features. These features are extracted based on distance transformation, and they are robust against changes in hand shape and self-occlusion. Finally, a `best view' image is selected for each hand for shape recognition. The shape recognition process is based on a Fourier descriptor. Our system can be used as a user interface device in a virtual environment, replacing glove-type devices and overcoming most of the disadvantages of contact-type devices.
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M3 - Chapter
AN - SCOPUS:0032655039
VL - 1
SP - 473
EP - 478
BT - Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
PB - IEEE
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