利用手掌和手指的运动作为基于手势的生物识别

M. Piekarczyk, M. Ogiela
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引用次数: 11

摘要

在本文中,我们考虑使用手掌运动作为有效的行为生物识别方式的可能性。我们建议利用从三维传感器设备收集的手部运动特征作为识别系统的输入数据。目前由于各种原因,人们担心直接接触生物识别扫描仪,因此非接触和非侵入性的方法似乎在实际应用中是有用的。在所描述的方案中,在执行定义的手势时,实时跟踪手掌和指尖的位置。提议的手势由空间排列的众所周知的符号组成,如字母和数字。所应用的匹配算法结合了DTW和DCT技术来比较数据序列。实验结果表明,该方法具有良好的应用前景。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
On Using Palm and Finger Movements as a Gesture-Based Biometrics
In this paper we consider possibility of using palm movements as effective behavioral biometric modality. We propose to exploit the hand motion characteristics gathered from 3D sensor device as input data for identification system. Currently for various reasons people are concerned about directly touching the biometric scanners, therefore touch-less and non-invasive approach seems to be useful in practical applications. In the described scheme palm and fingertip positions are tracked in real-time, while the defined gesture is performed. The proposed gesture is composed of the spatially arranged well-known signs like letters and numbers. The applied matching algorithm utilizes a combination of DTW and DCT techniques for comparing data series. The experiments show promising results using the proposed method.
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