Search results for "SOURCE LOCALIZATION"
showing 7 items of 17 documents
Real-time Sound Source Localization on Graphics Processing Units
2013
Abstract Sound source localization is an important topic in microphone array signal processing applications, such as camera steering systems, human-machine interaction or surveillance systems. The Steered Response Power with Phase Transform (SRP- PHAT) algorithm is one of the most well-known approaches for sound source localization due to its good performance in noisy and reverberant environments. The algorithm analyzes the sound power captured by a microphone array on a grid of spatial points in a given room. While localization accuracy can be improved by using a high resolution spatial grid and a high number of microphones, performing the localization task in these circumstances requires …
On the performance of multi-GPU-based expert systems for acoustic localization involving massive microphone arrays
2015
Sound source localization is an important topic in expert systems involving microphone arrays, such as automatic camera steering systems, human-machine interaction, video gaming or audio surveillance. The Steered Response Power with Phase Transform (SRP-PHAT) algorithm is a well-known approach for sound source localization due to its robust performance in noisy and reverberant environments. This algorithm analyzes the sound power captured by an acoustic beamformer on a defined spatial grid, estimating the source location as the point that maximizes the output power. Since localization accuracy can be improved by using high-resolution spatial grids and a high number of microphones, accurate …
Study of 3D sound for an audio-visual interaction in enriched virtual environment
2011
Most of the applications integrating 3D sound in virtual environment are limited to acoustic simulation. The objective of this thesis is to study the added value of 3D sound in the interaction with virtual environment. We developed an audio stimulation technique called "Artificial Spatial Audio Sensation: (ASAS)" based on the creation of audio effects. This technique conveys the sensations of spatialized sound that allows accurate sound source localization in azimuth and in elevation. In order to improve the localization time we also developed a model that integrates Head-Related Transfer Function (HRTF) with the ASAS technique. For the simulation of the depth of spatial sound sources, we d…
Microphones’ Directivity for the Localization of Sound Sources
2011
In a recent paper [P. Rizzo, G. Bordoni, A. Marzani, and J. Vipperman, "Localization of Sound Sources by Means of Unidirectional Microphones, Meas. Sci. Tech., 20, 055202 (12pp), 2009] the proof-of-concept of an approach for the localization of acoustic sources was presented. The method relies on the use of unidirectional microphones and amplitude-based signals' features to extract information about the direction of the incoming sound. By intersecting the directions identified by a pair of microphones, the position of the emitting source can be identified. In this paper we expand the work presented previously by assessing the effectiveness of the approach for the localization of an acoustic…
Design and Implementation of Acoustic Source Localization on a Low-Cost IoT Edge Platform
2020
The implementation of algorithms for acoustic source localization on edge platforms for the Internet of Things (IoT) is gaining momentum. Applications based on acoustic monitoring can greatly benefit from efficient implementations of such algorithms, enabling novel services for smart homes and buildings or ambient-assisted living. In this context, this brief proposes extreme low-cost sound source localization system composed of two microphones and the low power microcontroller module ESP32. A Direction-Of-Arrival (DOA) algorithm has been implemented taking into account the specific features of this board, showing excellent performance despite the memory constraints imposed by the platform. …
Connectivity Analysis in EEG Data: A Tutorial Review of the State of the Art and Emerging Trends
2023
Understanding how different areas of the human brain communicate with each other is a crucial issue in neuroscience. The concepts of structural, functional and effective connectivity have been widely exploited to describe the human connectome, consisting of brain networks, their structural connections and functional interactions. Despite high-spatial-resolution imaging techniques such as functional magnetic resonance imaging (fMRI) being widely used to map this complex network of multiple interactions, electroencephalographic (EEG) recordings claim high temporal resolution and are thus perfectly suitable to describe either spatially distributed and temporally dynamic patterns of neural acti…
Measuring the Task Induced Oscillatory Brain Activity Using Tensor Decomposition
2019
The characterization of dynamic electrophysiological brain activity, which form and dissolve in order to support ongoing cognitive function, is one of the most important goals in neuroscience. Here, we introduce a method with tensor decomposition for measuring the task-induced oscillations in the human brain using electroencephalography (EEG). The time frequency representation of source-reconstructed singletrail EEG data constructed a third-order tensor with three factors of time ∗ trails, frequency and source points. We then used a non-negative Canonical Polyadic decomposition (NCPD) to identify the temporal, spectral and spatial changes in electrophysiological brain activity. We validate …