The Experts below are selected from a list of 2019 Experts worldwide ranked by ideXlab platform
Athanasios Mouchtaris - One of the best experts on this subject based on the ideXlab platform.
-
Localizing multiple audio sources in a wireless acoustic sensor network
Signal Processing, 2015Co-Authors: Anthony Griffin, Despoina Pavlidi, Yiannis Mastorakis, Anastasios Alexandridis, Athanasios MouchtarisAbstract:In this work, we propose a Grid-Based Method to estimate the location of multiple sources in a wireless acoustic sensor network, where each sensor node contains a microphone array and only transmits direction-of-arrival (DOA) estimates in each time interval, reducing the transmissions to the central processing node. We present new work on modeling the DOA estimation error in such a scenario. Through extensive, realistic simulations, we show that our Method outperforms other state-of-the-art Methods, in both accuracy and complexity. We also present localization results of real recordings in an outdoor cell of a sensor network.
-
Real-time localization of multiple audio sources in a wireless acoustic sensor network
2014 22nd European Signal Processing Conference (EUSIPCO), 2014Co-Authors: Anthony Griffin, Despoina Pavlidi, Anastasios Alexandridis, Athanasios MouchtarisAbstract:In this work we propose a Grid-Based Method to estimate the location of multiple sources in a wireless acoustic sensor network, where each sensor node contains a microphone array and only transmits direction-of-arrival (DOA) estimates in each time interval, minimizing the transmissions to the central processing node. We present new work on modeling the DOA estimation error in such a scenario. Through extensive, realistic simulations, we show our Method outperforms other state-of-the-art Methods, in both accuracy and complexity. We present localization results of real recordings in an outdoor cell of a sensor network.
Anthony Griffin - One of the best experts on this subject based on the ideXlab platform.
-
Localizing multiple audio sources in a wireless acoustic sensor network
Signal Processing, 2015Co-Authors: Anthony Griffin, Despoina Pavlidi, Yiannis Mastorakis, Anastasios Alexandridis, Athanasios MouchtarisAbstract:In this work, we propose a Grid-Based Method to estimate the location of multiple sources in a wireless acoustic sensor network, where each sensor node contains a microphone array and only transmits direction-of-arrival (DOA) estimates in each time interval, reducing the transmissions to the central processing node. We present new work on modeling the DOA estimation error in such a scenario. Through extensive, realistic simulations, we show that our Method outperforms other state-of-the-art Methods, in both accuracy and complexity. We also present localization results of real recordings in an outdoor cell of a sensor network.
-
Real-time localization of multiple audio sources in a wireless acoustic sensor network
2014 22nd European Signal Processing Conference (EUSIPCO), 2014Co-Authors: Anthony Griffin, Despoina Pavlidi, Anastasios Alexandridis, Athanasios MouchtarisAbstract:In this work we propose a Grid-Based Method to estimate the location of multiple sources in a wireless acoustic sensor network, where each sensor node contains a microphone array and only transmits direction-of-arrival (DOA) estimates in each time interval, minimizing the transmissions to the central processing node. We present new work on modeling the DOA estimation error in such a scenario. Through extensive, realistic simulations, we show our Method outperforms other state-of-the-art Methods, in both accuracy and complexity. We present localization results of real recordings in an outdoor cell of a sensor network.
Anastasios Alexandridis - One of the best experts on this subject based on the ideXlab platform.
-
Localizing multiple audio sources in a wireless acoustic sensor network
Signal Processing, 2015Co-Authors: Anthony Griffin, Despoina Pavlidi, Yiannis Mastorakis, Anastasios Alexandridis, Athanasios MouchtarisAbstract:In this work, we propose a Grid-Based Method to estimate the location of multiple sources in a wireless acoustic sensor network, where each sensor node contains a microphone array and only transmits direction-of-arrival (DOA) estimates in each time interval, reducing the transmissions to the central processing node. We present new work on modeling the DOA estimation error in such a scenario. Through extensive, realistic simulations, we show that our Method outperforms other state-of-the-art Methods, in both accuracy and complexity. We also present localization results of real recordings in an outdoor cell of a sensor network.
-
Real-time localization of multiple audio sources in a wireless acoustic sensor network
2014 22nd European Signal Processing Conference (EUSIPCO), 2014Co-Authors: Anthony Griffin, Despoina Pavlidi, Anastasios Alexandridis, Athanasios MouchtarisAbstract:In this work we propose a Grid-Based Method to estimate the location of multiple sources in a wireless acoustic sensor network, where each sensor node contains a microphone array and only transmits direction-of-arrival (DOA) estimates in each time interval, minimizing the transmissions to the central processing node. We present new work on modeling the DOA estimation error in such a scenario. Through extensive, realistic simulations, we show our Method outperforms other state-of-the-art Methods, in both accuracy and complexity. We present localization results of real recordings in an outdoor cell of a sensor network.
Despoina Pavlidi - One of the best experts on this subject based on the ideXlab platform.
-
Localizing multiple audio sources in a wireless acoustic sensor network
Signal Processing, 2015Co-Authors: Anthony Griffin, Despoina Pavlidi, Yiannis Mastorakis, Anastasios Alexandridis, Athanasios MouchtarisAbstract:In this work, we propose a Grid-Based Method to estimate the location of multiple sources in a wireless acoustic sensor network, where each sensor node contains a microphone array and only transmits direction-of-arrival (DOA) estimates in each time interval, reducing the transmissions to the central processing node. We present new work on modeling the DOA estimation error in such a scenario. Through extensive, realistic simulations, we show that our Method outperforms other state-of-the-art Methods, in both accuracy and complexity. We also present localization results of real recordings in an outdoor cell of a sensor network.
-
Real-time localization of multiple audio sources in a wireless acoustic sensor network
2014 22nd European Signal Processing Conference (EUSIPCO), 2014Co-Authors: Anthony Griffin, Despoina Pavlidi, Anastasios Alexandridis, Athanasios MouchtarisAbstract:In this work we propose a Grid-Based Method to estimate the location of multiple sources in a wireless acoustic sensor network, where each sensor node contains a microphone array and only transmits direction-of-arrival (DOA) estimates in each time interval, minimizing the transmissions to the central processing node. We present new work on modeling the DOA estimation error in such a scenario. Through extensive, realistic simulations, we show our Method outperforms other state-of-the-art Methods, in both accuracy and complexity. We present localization results of real recordings in an outdoor cell of a sensor network.
Yiannis Mastorakis - One of the best experts on this subject based on the ideXlab platform.
-
Localizing multiple audio sources in a wireless acoustic sensor network
Signal Processing, 2015Co-Authors: Anthony Griffin, Despoina Pavlidi, Yiannis Mastorakis, Anastasios Alexandridis, Athanasios MouchtarisAbstract:In this work, we propose a Grid-Based Method to estimate the location of multiple sources in a wireless acoustic sensor network, where each sensor node contains a microphone array and only transmits direction-of-arrival (DOA) estimates in each time interval, reducing the transmissions to the central processing node. We present new work on modeling the DOA estimation error in such a scenario. Through extensive, realistic simulations, we show that our Method outperforms other state-of-the-art Methods, in both accuracy and complexity. We also present localization results of real recordings in an outdoor cell of a sensor network.
