抄録
J-049
見えの変形を学習させた分類木に基づく高精度実時間三次元手指姿勢推定
◎宮本　翔（立命館大）・藤本光一（東芝ソリューション）・松尾直志・島田伸敬・白井良明（立命館大）
We propose a method for estimating 3-D hand postures from 2-D images in real-time. The estimation is based on finding the best matched posture from typical postures whose appearances are learned in advance. For high accuracy, conventional methods require high computational cost for comparing an input with many typical postures. In our method, a tree is automatically generated and trained with typical postures and their variations. Efficient search with the tree brings about real-time estimation. We show the effectiveness of our method by some experimental results.