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Acoustic Reflector Localization: Novel Image Source Reversion and Direct Localization Methods

机译:声反射器定位:新颖的图像源还原和直接定位方法

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摘要

Acoustic reflector localization is an important issue in audio signal processing, with direct applications in spatial audio, scene reconstruction, and source separation. Several methods have recently been proposed to estimate the 3D positions of acoustic reflectors given room impulse responses (RIRs). In this article, we categorize these methods as “image-source reversion”, which localizes the image source before finding the reflector position, and “direct localization”, which localizes the reflector without intermediate steps. We present five new contributions. First, an onset detector, called the clustered dynamic programming projected phase-slope algorithm, is proposed to automatically extract the time of arrival for early reflections within the RIRs of a compact microphone array. Second, we propose an image-source reversion method that uses the RIRs from a single loudspeaker. It is constructed by combining an image source locator (the image source direction and range (ISDAR) algorithm), and a reflector locator (using the loudspeaker-image bisection (LIB) algorithm). Third, two variants of it, exploiting multiple loudspeakers, are proposed. Fourth, we present a direct localization method, the ellipsoid tangent sample consensus (ETSAC), exploiting ellipsoid properties to localize the reflector. Finally, systematic experiments on simulated and measured RIRs are presented, comparing the proposed methods with the state-of-the-art. ETSAC generates errors lower than the alternative methods compared through our datasets. Nevertheless, the ISDAR-LIB combination performs well and has a run time 200 times faster than ETSAC.
机译:声学反射器的本地化是音频信号处理中的一个重要问题,它直接应用于空间音频,场景重建和源分离。最近已经提出了几种方法来估计给定房间脉冲响应(RIR)的声反射器的3D位置。在本文中,我们将这些方法分为“图像源反转”和“直接定位”,其中“图像源反转”在找到反射器位置之前先对图像源进行定位,而“直接定位”则在没有中间步骤的情况下对反射器进行定位。我们提出了五项新的贡献。首先,提出了一种称为聚类动态规划投影相位斜率算法的启动检测器,可以自动提取紧凑麦克风阵列的RIR内的早期反射的到达时间。其次,我们提出一种图像源还原方法,该方法使用来自单个扬声器的RIR。它是通过组合图像源定位器(图像源方向和范围(ISDAR)算法)和反射器定位器(使用扬声器图像对分(LIB)算法)而构造的。第三,提出了利用多个扬声器的两个变体。第四,我们提出了一种直接的定位方法,即椭球切线样本共有量(ETSAC),它利用椭球特性来定位反射器。最后,将模拟和测量的RIR进行了系统的实验,并将所提出的方法与最新技术进行了比较。与我们的数据集相比,ETSAC产生的误差低于其他方法。不过,ISDAR-LIB组合的性能良好,运​​行时间比ETSAC快200倍。

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