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.
本文言語 | English |
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ページ(範囲) | 473-478 |
ページ数 | 6 |
ジャーナル | Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition |
巻 | 1 |
出版ステータス | Published - 1999 1月 1 |
外部発表 | はい |
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月 23 → 1999 6月 25 |
ASJC Scopus subject areas
- ソフトウェア
- コンピュータ ビジョンおよびパターン認識