Recognition of shape-changing hand gestures

被引:0
|
作者
Jeong, MH
Kuno, Y
Shimada, N
Shirai, Y
机构
[1] Osaka Univ, Dept Mech Engn Comp Controlled Machinery, Suita, Osaka 5650871, Japan
[2] Saitama Univ, Fac Engn, Dept Informat & Comp Sci, Saitama 3388570, Japan
来源
关键词
gesture recognition; active contour; switching linear model;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
We present a method to track and recognize shape-changing hand gestures simultaneously. The switching linear model using active contour model well corresponds to temporal shapes and motions of hands. However, inference in the switching linear model is computationally intractable, and therefore the learning process cannot be performed via the exact EM(Expectation Maximization) algorithm. Thus, we present an approximate EM algorithm using a collapsing method in which some Gaussians are merged into a single Gaussian. Tracking is performed through the forward algorithm based on Kalman filtering and the collapsing method. We also present a regularized smoothing, which plays a role of reducing jump changes between the training sequences of shape vectors representing complex-variable hand shapes. The recognition process is performed by the selection of a model with the maximum likelihood from some trained models while tracking is being performed. Experiments for several shape-changing hand gestures are demonstrated.
引用
收藏
页码:1678 / 1687
页数:10
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