Automatic recognition of hand gestures with differential evolution

被引：0
|
作者：
De Falco, I. [1 ]
Della Cioppa, A. [2 ]
Maisto, D. [1 ]
Scafuri, U. [1 ]
Tarantino, E. [1 ]
机构：
[1] ICAR CNR, Via P Castellino 111, I-80131 Naples, Italy
[2] Univ Salerno, DIIIE Lab, I-84084 Salerno, Italy
来源：
APPLICATIONS OF EVOLUTIONARY COMPUTING, PROCEEDINGS | 2008年 / 4974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：
Automatic recognition of hand gestures is a crucial step in facing human-computer interaction. Differential Evolution is used to perform automatic classification of hand gestures in a thirteen-class database. Performance of the resulting best individual is computed in terms of error rate on the testing set, and is compared against those of other ten classification techniques well known in literature. Results show the effectiveness and the efficiency of the approach in solving the classification task. Furthermore, the implemented tool allows to extract the most significant parameters for differentiating the collected gestures.
引用
收藏
页码：265 / +
页数：2
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