Fuzzy rule-based hand gesture recognition

被引：0
|
作者：
Bedregal, Benjamin C. [1 ]
Costa, Antonio C. R. [2 ]
Dimuro, Gracaliz P. [2 ]
机构：
[1] Univ Fed Rio Grande do Norte, Dept Informat & Appl Math, BR-59072970 Natal, RN, Brazil
[2] Catholic Univ, Informat Sch, Grad Programme Comp Sci, Pelotas, Brazil
来源：
ARTIFICIAL INTELLIGENCE IN THEORY AND PRACTICE | 2006年 / 217卷
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper introduces a fuzzy rule-based method for the recognition of hand gestures acquired from a data glove, with an application to the recognition of some sample hand gestures of LIBRAS, the Brazilian Sign Language. The method uses the set of angles of finger joints for the classification of hand configurations, and classifications of segments of hand gestures for recognizing gestures. The segmentation of gestures is based on the concept of monotonic gesture segment, sequences of hand configurations in which the variations of the angles of the finger joints have the same sign (non-increasing or non-decreasing). Each gesture is characterized by its list of monotonic segments. The set of all lists of segments of a given set of gestures determine a set of finite automata, which are able to recognize every such gesture.
引用
收藏
页码：285 / +
页数：2
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