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A natural approach to convey numerical digits using hand activity recognition based on hand shape features

机译:一种基于手形状特征的手动活动识别传达数值的自然方法

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This paper presents a natural representation of numerical digit(s) using hand activity analysis based on number of fingers out stretched for each numerical digit in sequence extracted from a video. The analysis is based on determining a set of six features from a hand image. The most important features used from each frame in a video are the first fingertip from top, palm-line, palm-center, valley points between the fingers exists above the palm-line. Using this work user can convey any number of numerical digits using right or left or both the hands naturally in a video. Each numerical digit ranges from 0 to9. Hands (right/left/both) used to convey digits can be recognized accurately using the valley points and with this recognition whether the user is a right/left handed person in practice can be analyzed. In this work, first the hand(s) and face parts are detected by using YCbCr color space and face part is removed by using ellipse based method. Then, the hand(s) are analyzed to recognize the activity that represents a series of numerical digits in a video. This work uses pixel continuity algorithm using 2D coordinate geometry system and does not use regular use of calculus, contours, convex hull and datasets.
机译:本文介绍了使用手动活动分析的数值的自然表示,该数量是基于从视频中提取的序列中的每个数值数字伸展的手指的数量。该分析基于确定来自手图像的一组六个特征。从视频中的每个帧中使用的最重要的功能是来自顶部,掌上线,掌心中心的第一个指尖,手指之间的谷点存在于掌上线上方。使用此工作用户可以使用右侧或左侧或双手在视频中使用任何数量的数值数字。每个数字数字从0到9的范围。用于传达数字的手(右/左/均)可以使用谷点准确识别,并通过这种识别来分析用户是否是右/左手的人。在这项工作中,首先通过使用基于椭圆的方法使用YCBCR颜色空间检测手和面部。然后,分析手以识别表示视频中的一系列数值数字的活动。这项工作使用使用2D坐标几何系统的像素连续性算法,不使用正常使用微积分,轮廓,凸壳和数据集。

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