Publications de Ivan Dokmanic | EPFL Graph Search

Localizing Unsynchronized Sensors With Unknown Sources

Ivan Dokmanic, Dalia Salem Hassan Fahmy El Badawy

We propose a method for sensor array self-localization using a set of sources at unknown locations. The sources produce signals whose times of arrival are registered at the sensors. We look at the general case where neither the emission times of the source ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023

Shapes From Echoes: Uniqueness From Point-to-Plane Distance Matrices

Martin Vetterli, Ivan Dokmanic, Miranda Krekovic

We study the problem of localizing a configuration of points and planes from the collection of point-to-plane distances. This problem models simultaneous localization and mapping from acoustic echoes as well as the & x201C;structure from sound & x201D; app ...

2020

Kinetic Euclidean Distance Matrices

Martin Vetterli, Ivan Dokmanic, Puoya Tabaghi

Euclidean distance matrices (EDMs) are a major tool for localization from distances, with applications ranging from protein structure determination to global positioning and manifold learning. They are, however, static objects which serve to localize point ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2020

On The Move: Localization With Kinetic Euclidean Distance Matrices

Martin Vetterli, Ivan Dokmanic, Puoya Tabaghi

In this paper, we propose kinetic Euclidean distance matrices (KEDMs) a new algebraic tool for localization of moving points from spatio temporal distance measurements. KEDMs are inspired by the well-known Euclidean distance matrices (EDM) which model stat ...

IEEE2019

Structure from sound with incomplete data

Martin Vetterli, Gilles Baechler, Ivan Dokmanic, Miranda Krekovic

In this paper, we consider the problem of jointly localizing a microphone array and identifying the direction of arrival of acoustic events. Under the assumption that the sources are in the far field, this problem can be formulated as a constrained low-ran ...

2018

Direction of Arrival with One Microphone, a few LEGOs, and Non-Negative Matrix Factorization

Ivan Dokmanic, Dalia Salem Hassan Fahmy El Badawy

Conventional approaches to sound source localization require at least two microphones. It is known, however, that people with unilateral hearing loss can also localize sounds. Monaural localization is possible thanks to the scattering by the head, though i ...

2018

Pyroomacoustics: A Python Package For Audio Room Simulation And Array Processing Algorithms

Robin Scheibler, Ivan Dokmanic, Eric Bezzam

We present pyroomacoustics, a software package aimed at the rapid development and testing of audio array processing algorithms. The content of the package can be divided into three main components: an intuitive Python object-oriented interface to quickly c ...

IEEE2018

Omnidirectional bats, point-to-plane distances, and the price of uniqueness

Martin Vetterli, Ivan Dokmanic, Miranda Krekovic

We study simultaneous localization and mapping with a device that uses reflections to measure its distance from walls. Such a device can be realized acoustically with a synchronized collocated source and receiver; it behaves like a bat with no capacity for ...

Ieee2017

Acoustic DoA Estimation by One Unsophisticated Sensor

Martin Vetterli, Ivan Dokmanic, Dalia Salem Hassan Fahmy El Badawy

We show how introducing known scattering can be used in direction of arrival estimation by a single sensor. We first present an analysis of the geometry of the underlying measurement space and show how it enables localizing white sources. Then, we extend t ...

Springer Verlag2017

Method and apparatus for presenting to a user of a wearable apparatus additional information related to an audio scene

Martin Vetterli, Juri Ranieri, Ivan Dokmanic

A method for presenting to a user of a wearable audio device a modified audio scene together with additional information related to the audio scene, comprising: capturing audio signals with a plurality of microphones; outputting an audio signal with a plur ...

2017

FRIDA: FRI-Based DOA Estimation For Arbitrary Array Layouts

Martin Vetterli, Robin Scheibler, Hanjie Pan, Ivan Dokmanic, Eric Bezzam

In this paper we present FRIDA—an algorithm for estimating directions of arrival of multiple wideband sound sources. FRIDA combines multi-band information coherently and achieves state- of-the-art resolution at extremely low signal-to-noise ratios. It work ...

IEEE2017

From Acoustic Room Reconstruction to SLAM

Martin Vetterli, Ivan Dokmanic

Recent works on reconstruction of room geometry from echoes assume that the geometry of the sensor array is known. In this paper, we show that such an assumption is not essential; echoes provide sufficient clues to reconstruct the room’s and the array’s ge ...

Ieee2016

Optimal acoustic rake receiver

Martin Vetterli, Robin Scheibler, Ivan Dokmanic

An acoustic processing method for M acoustic receivers comprising the steps of: Determining a beamforming weight vector with M weights for the M acoustic receivers based on at least one the steering vector of at least one real acoustic source, on steering ...

2016

Relax and Unfold: Microphone Localization with Euclidean Distance Matrices

Martin Vetterli, Juri Ranieri, Ivan Dokmanic

Recent methods for localization of microphones in a microphone array exploit sound sources at a priori unknown locations. This is convenient for ad-hoc arrays, as it requires little additional infrastructure. We propose a flexible localization algorithm by ...

2015

Listening to Distances and Hearing Shapes : Inverse Problems in Room Acoustics and Beyond

Ivan Dokmanic

A central theme of this thesis is using echoes to achieve useful, interesting, and sometimes surprising results. One should have no doubts about the echoes' constructive potential; it is, after all, demonstrated masterfully by Nature. Just think about the ...

EPFL2015

Euclidean Distance Matrices: Essential Theory, Algorithms and Applications

Martin Vetterli, Reza Parhizkar, Juri Ranieri, Ivan Dokmanic

Euclidean distance matrices (EDMs) are matrices of the squared distances between points. The definition is deceivingly simple; thanks to their many useful properties, they have found applications in psychometrics, crystallography, machine learning, wireles ...

2015

Raking the Cocktail Party

Martin Vetterli, Robin Scheibler, Ivan Dokmanic

We present the concept of an acoustic rake receiver—a microphone beamformer that uses echoes to improve the noise and interference suppression. The rake idea is well-known in wireless communications; it involves constructively combining different multipath ...

Ieee-Inst Electrical Electronics Engineers Inc2015

OMP with Unknown Filters for Multipath Channel Estimation

Martin Vetterli, Ivan Dokmanic

We study a modification of the orthogonal matching pursuit (OMP) for estimating sparse multipath channels. The reflectors that generate the multipath components are not ideal; rather, they act as filters, so that the returned pulses are reshaped and widene ...

2015

Single-Channel Indoor Microphone Localization

Martin Vetterli, Reza Parhizkar, Ivan Dokmanic

We propose a novel method for single-channel microphone localization inside a known room. Unlike other approaches, we take advantage of the room reverberation, which enables us to use only a single fixed loudspeaker to localize the microphone. Our method u ...

IEEE2014

Source Localization and Tracking in Non-Convex Rooms

Martin Vetterli, Ivan Dokmanic, Orhan Öçal

We consider the estimation of the acoustic source position in a known room from recordings by a microphone array. We propose an algorithm that does not require the room to be convex, nor a line-of-sight path between the microphone array and the source to b ...

Ieee2014