Personne

Ivan Dokmanic

Cette personne n’est plus à l’EPFL

Publications associées (29)

Calibration method and system

The present invention concerns a method for calibrating an array of receivers (ri), each receiver being configured for receiving a signal transmitted by at least one transmitter (si), and echoes of the transmitted signal as reflected by one or more reflect ...

2014

Hardware and Algorithms for Ultrasonic Depth Imaging

Ivan Dokmanic

Depth imaging is commonly based on light. For example, LIDAR and Kinect use infrared light, while stereo cameras use visible light. These systems require hardware operating at high sampling frequencies, precise calibration, and they dissipate significant p ...

Ieee2014

How to Localize Ten Microphones in One Fingersnap

Martin Vetterli, Ivan Dokmanic

A compelling method to calibrate the positions of microphones in an array is with sources at unknown locations. Remarkably, it is possible to reconstruct the locations of both the sources and the receivers, if their number is larger than some prescribed mi ...

IEEE2014

The Fukushima Inverse Problem

Martin Vetterli, Robin Scheibler, Juri Ranieri, Ivan Dokmanic, Marta Martinez-Camara

Knowing what amount of radioactive material was released from Fukushima in March 2011 and at what time instants is crucial to assess the risk, the pollution, and to understand the scope of the consequences. Moreover, it could be used in forward simulations ...

2013

Acoustic Echoes Reveal Room Shape

Martin Vetterli, Reza Parhizkar, Yue Lu, Andreas Walther, Ivan Dokmanic

Imagine that you are blindfolded inside an unknown room. You snap your fingers and listen to the room’s response. Can you hear the shape of the room? Some people can do it naturally, but can we design computer algorithms that hear rooms? We show how to com ...

National Academy of Sciences2013

Room Helps: Acoustic Localization With Finite Elements

Martin Vetterli, Ivan Dokmanic

Acoustic source localization often relies on the free-space/far-field model. Recent work exploiting spatio-temporal sparsity promises to go beyond these scenarios, however, it requires the knowledge of the transfer functions from each possible source locat ...

Ieee2012

Sampling and Reconstruction of Time-Varying Atmospheric Emissions

Martin Vetterli, Amina Chebira, Juri Ranieri, Ivan Dokmanic

We study the spatio-temporal sampling of physical fields representing the dispersion of a substance in the atmosphere. We consider the following setup: N sensors are deployed at ground level and measure the concentration of a particular substance, while M ...

Ieee2012

Sensor Networks for Diffusion Fields: Detection of Sources in Space and Time

Martin Vetterli, Amina Chebira, Juri Ranieri, Ivan Dokmanic

We consider the problem of reconstructing a diffusion field, such as temperature, from samples collected by a sensor network. Motivated by the fast decay of the eigenvalues of the diffusion equation, we approximate the field by a truncated series. We show ...

2011

Can One Hear the Shape of a Room: The 2–D Polygonal Case

Martin Vetterli, Yue Lu, Ivan Dokmanic

We consider the problem of estimating room geometry from the acoustic room impulse response (RIR). Existing approaches addressing this problem exploit the knowledge of multiple RIRs. In contrast, we are interested in reconstructing the room geometry from a ...

Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa2011