基于小样本学习的3D 动态视觉手势个性化交互方法

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	基于小样本学习的3D 动态视觉手势个性化交互方法
	武汇岳 ; 王建民 ; 戴国忠
刊名	电子学报
	2013
卷号	41 期号:11 页码:2230-2236
关键词	人机交互视觉手势小样本学习个性化交互 human-computer interaction vision-based gestures small sample learning personalized interaction
ISSN号	0372-2112
其他题名	Personalized Interaction Techniques of Vision-Based 3D Dynamic Gestures Based on Small Sample Learning
中文摘要	传统的动态手势交互技术如隐马尔科夫模型、神经网络和统计分类器等都需要大量的训练样本，建模过程中需要领域专家的干预、对普通用户来说使用起来较为困难，并且它们针对的是特定的手势集合，很难对其进行扩展。本文通过WOZ实验，分析了用户的行为特征并给出了基于手势的数字电视交互任务模型；提出了3D动态手势状态转移模型，解决了Midas Touch问题；提出了一种基于小样本学习的动态手势识别方法，解决了传统手势识别方法的缺点；构建了个性化手势设计平台，满足了用户的个性化定制需求；实验评估结果验证了本文方法的有效性。 There are some unresolved issues left behind for many traditional dynamic gesture recognition methods ,such as Hidden Markov Model(HMM) ,Neural Network(NN) ,and statistical classifiers .For example ,they require a large number of train-ing examples and the involvement of expert users in the training process .Moreover ,they are used for some specific gesture sets which are difficult to be extended .In this paper ,we first build a task model and a state transition model for vision-based dynamic gestures .Then we propose a method for 3D dynamic gesture recognition based on small sample learning .Next we design a toolkit for development of user-defined gestures .Finally ,we develop a gesture-based interactive television prototype .Experimental results verify the validity of our method .
英文摘要	There are some unresolved issues left behind for many traditional dynamic gesture recognition methods, such as Hidden Markov Model(HMM), Neural Network(NN), and statistical classifiers. For example, they require a large number of training examples and the involvement of expert users in the training process. Moreover, they are used for some specific gesture sets which are difficult to be extended. In this paper, we first build a task model and a state transition model for vision-based dynamic gestures. Then we propose a method for 3D dynamic gesture recognition based on small sample learning. Next we design a toolkit for development of user-defined gestures. Finally, we develop a gesture-based interactive television prototype. Experimental results verify the validity of our method.
收录类别	CSCD
语种	中文
CSCD记录号	CSCD:5018279
公开日期	2014-12-16
内容类型	期刊论文
源URL	[http://ir.iscas.ac.cn/handle/311060/16781]
专题	软件研究所_软件所图书馆_期刊论文
推荐引用方式 GB/T 7714	武汇岳,王建民,戴国忠. 基于小样本学习的3D 动态视觉手势个性化交互方法[J]. 电子学报,2013,41(11):2230-2236.
APA	武汇岳,王建民,&戴国忠.(2013).基于小样本学习的3D 动态视觉手势个性化交互方法.电子学报,41(11),2230-2236.
MLA	武汇岳,et al."基于小样本学习的3D 动态视觉手势个性化交互方法".电子学报 41.11(2013):2230-2236.