Sound-based classification of objects using a robust fingerprinting approach
Sound-based classification of objects using a robust fingerprinting approach
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使用稳健的指纹识别方法对物体进行基于声音的分类
DOI：
10.5281/zenodo.40679
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发表时间：
2007
期刊：
影响因子：
--
通讯作者：
G. Valenzise
中科院分区：
文献类型：
--
作者：
F. Antonacci;L. Gerosa;A. Sarti;S. Tubaro;G. Valenzise
声界面（TAI）是一种能够定位固体表面上相互作用点的相互作用装置。它们相对于传统交互设备（触摸屏、触摸板等）的优势实际的声学（振动）信号是由接触传感器获取的。这为交互分类和识别开辟了道路。考虑到这一应用，本文探讨了从所获得的声音的交互对象的分类问题。我们专注于连续的相互作用噪声，我们通过“指纹识别”方法进行分类：从采集的信号中提取特征，并与预先计算的特征进行匹配。更复杂的解决方案，可以设计的问题的分类noiselike声音，但我们的方法具有计算简单的优点，可以有利地实现实时。
Tangible Acoustic Interfaces (TAIs) are interaction devices that are able to localize the interaction point on a solid surface. Their advantages over traditional interaction devices (touch screens, touch pads, etc.) is in the fact that actual acoustic (vibrational) signals are acquired by contact sensors. This opens the way to interaction classification and recognition. With this application in mind, this paper approaches the problem of classifying the interaction object from the acquired sounds. We focus on continuous interaction noise, which we classify through a “fingerprinting” approach: features are extracted from the acquired signals and matched against pre-computed features. More sophisticated solutions can be devised for the problem of the classification of noiselike sounds but our approach has the advantage of being computationally simple and can be profitably implemented in real-time.