Neural-network-based real-time human body posture estimation

Kazuhiko Takahashi*, Tetsuya Uemura, Jun Ohya


研究成果: Paper査読

3 被引用数 (Scopus)


This paper proposes a real-time human body posture estimation method using ANNs. The network is composed of three ANNs and a decision logic unit. The ANNs' input is the result of a function analysis on a human silhouette's contour extracted from camera images and the ANNs' output indicates the feature points' positions on the contour. The decision logic unit synthesizes each of the ANNs' output vectors and then the 2D coordinates of the human body's feature points are calculated. The proposed method is implemented on a personal computer and runs in real-time (17-20 frames/sec). Experimental results confirm both the feasibility and the effectiveness of the proposed method for estimating human body postures.

出版ステータスPublished - 2000 12月 1
イベント10th IEEE Workshop on Neural Network for Signal Processing (NNSP2000) - Sydney, Australia
継続期間: 2000 12月 112000 12月 13


Other10th IEEE Workshop on Neural Network for Signal Processing (NNSP2000)
CitySydney, Australia

ASJC Scopus subject areas

  • 信号処理
  • ソフトウェア
  • 電子工学および電気工学


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