Online Hand Gesture Recognition Using Neural Network Based Segmentation

被引：9
|
作者：
Zhu, Chun [1 ]
Sheng, Weihua [1 ]
机构：
[1] Oklahoma State Univ, Sch Elect & Comp Engn, Stillwater, OK 74078 USA
来源：
2009 IEEE-RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS | 2009年
关键词：
Gesture Recognition; Assisted Living; Wearable Sensor;
D O I：
10.1109/IROS.2009.5354657
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, we propose an online hand gesture recognition algorithm for a robot assisted living system. A neural network-based gesture spotting method is combined with the hierarchical hidden Markov model (HHMM) to recognize hand gestures. In the segmentation module, the neural network is used to determine whether the HHMM-based recognition module should be applied. In the recognition module, Bayesian filtering is applied to update the results considering the context constraints. We implemented the algorithm using an inertial sensor worn on a finger of the human subject. The obtained results prove the accuracy and effectiveness of our algorithm.
引用
收藏
页码：2415 / 2420
页数：6
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