查询结果:   张军,张孔,杨正瓴.基于计算机视觉的多特征手势识别[J].计算机应用与软件,2016,33(6):151 - 154,189.
中文标题
基于计算机视觉的多特征手势识别
发表栏目
人工智能与识别
摘要点击数
799
英文标题
COMPUTER VISION-BASED RECOGNITION OF HAND GESTURE WITH MULTIPLE FEATURES
作 者
张军 张孔 杨正瓴 Zhang Jun Zhang Kong Yang Zhengling
作者单位
天津大学电气与自动化工程学院 天津 300072     
英文单位
School of Electrical and Automation Engineering,Tianjin University,Tianjin 300072,China     
关键词
计算机视觉 手势识别 空间曲率特征 Hu不变矩 神经网络
Keywords
Computer vision Hand gesture recognition CSS Hu invariant moment Neural network
基金项目
天津市创新基金项目(13ZXCXGX404 00)
作者资料
张军,副教授,主研领域:图像处理,智能交通。张孔,硕士生。杨正瓴,副教授。 。
文章摘要
目前常用单特征手势识别方法中,缺少完整的手势轮廓信息,对局部相似度高和形状复杂的手势识别率较低,为此提出一种将CSS特征描述子与Hu不变矩相结合的手势特征提取方法。首先,利用肤色模型把手势从复杂的背景中提取出来,然后分别提取手势的Hu不变矩和CSS描述子来构建融合特征,最后利用人工神经网络对新特征进行识别和分类。实验结果表明,与基于单一特征的识别方法相比,该方法整体识别率更高,对局部形似度高的手势识别率有很大提升。
Abstract
Because of lacking full hand gestures contour information, current commonly used hand gesture recognition algorithms using single feature have lower recognition rate for the gestures with high local similarity and complicated shapes. Therefore we proposed a novel hand gesture feature extraction method, which combines the feature descriptor of curvature scale space (CSS) with Hu invariant moment. First, we used the skin colour model to extract the gestures from complicated background, and then extracted Hu invariant moment and CSS descriptor of gestures respectively to construct fusion features. At last, we made use of the artificial neural network to recognise and classify the new features. Experimental results demonstrated that compared with the recognition approaches based on single gesture feature, the proposed method has higher integral recognition rate, and improves significantly in recognition rate on gestures with high local similarity in shape.
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