Publications by Martin Vetterli

The recursive Hessian sketch for adaptive filtering

We introduce in this paper the recursive Hessian sketch, a new adaptive filtering algorithm based on sketching the same exponentially weighted least squares problem solved by the recursive least squares algorithm. The algorithm maintains a number of sketch ...

Ieee2016

EchoSLAM: Simultaneous Localization and Mapping with Acoustic Echoes

Martin Vetterli, Ivan Dokmanic, Miranda Krekovic

We address the problem of jointly localizing a robot in an unknown room and estimating the room geometry from echoes. Unlike earlier work using echoes, we assume a completely autonomous setup with (near) collocated microphone and the acoustic source. We fi ...

Ieee2016

Where You Are is Who You Are: User Identification by Matching Statistics

Martin Vetterli, Patrick Thiran, Jayakrishnan Unnikrishnan, Farid Movahedi Naini

Most users of online services have unique behavioral or usage patterns. These behavioral patterns can be used to identify and track users by using only the observed patterns in the behavior. We study the task of identifying users from statistics of their b ...

Institute of Electrical and Electronics Engineers2016

Shapes from pixels

Martin Vetterli, Arash Amini, Loïc Arnaud Baboulaz, Mitra Fatemi

Continuous-domain visual signals are usually captured as discrete (digital) images. This operation is not invertible in general, in the sense that the continuous-domain signal cannot be exactly reconstructed based on the discrete image, unless it satisfies ...

Institute of Electrical and Electronics Engineers2016

VITRAIL : Acquisition, Modelling and Rendering of Stained Glass

Martin Vetterli, Paolo Prandoni, Loïc Arnaud Baboulaz, Niranjan Thanikachalam

Stained glass windows are designed to reveal their powerful artistry under diverse and time-varying lighting conditions; virtual relighting of stained glass, therefore represents an exceptional tool for the appreciation of this age old art form. However, a ...

Institute of Electrical and Electronics Engineers2016

Learning Network Structures from Firing Patterns

Martin Vetterli, Amin Karbasi, Amir Hesam Salavati

How can we decipher the hidden structure of a network based on limited observations? This question arises in many scenarios ranging from social to wireless and to neural networks. In such settings, we typically observe the nodes’ behaviors (e.g., the time ...

Ieee2016

Sampling and Reconstruction of Shapes with Algebraic Boundaries

Martin Vetterli, Arash Amini, Mitra Fatemi

We present a sampling theory for a class of binary images with finite rate of innovation (FRI). Every image in our model is the restriction of

\mathds{1}_{\{p\leq0\}}

to the image plane, where

\mathds{1}

denotes the indicator function and

p

is some r ...

2016

SHAPE: Linear-Time Camera Pose Estimation With Quadratic Error-Decay

Martin Vetterli, Adam James Scholefield, Alireza Ghasemi

We propose a novel camera pose estimation or perspective-n-point (PnP) algorithm, based on the idea of consistency regions and half-space intersections. Our algorithm has linear time-complexity and a squared reconstruction error that decreases at least qua ...

Ieee2016

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

Accurate recovery of a specularity from a few samples of the reflectance function

Martin Vetterli, Ivan Dokmanic, Loïc Arnaud Baboulaz, Gilles Baechler

We present a new technique for estimating the specular peak of the bidirectional reflectance distribution function (BRDF) based on finite rate of innovation (FRI) sampling. The specular component of the BRDF varies rapidly, so it is challenging to acquire ...

Ieee2016

Martin Vetterli

Graph Chatbot

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The recursive Hessian sketch for adaptive filtering

EchoSLAM: Simultaneous Localization and Mapping with Acoustic Echoes

Where You Are is Who You Are: User Identification by Matching Statistics

Shapes from pixels

VITRAIL : Acquisition, Modelling and Rendering of Stained Glass

Learning Network Structures from Firing Patterns

Sampling and Reconstruction of Shapes with Algebraic Boundaries

SHAPE: Linear-Time Camera Pose Estimation With Quadratic Error-Decay

From Acoustic Room Reconstruction to SLAM

Accurate recovery of a specularity from a few samples of the reflectance function

EchoSLAM: Simultaneous Localization and Mapping with Acoustic Echoes

Accurate recovery of a specularity from a few samples of the reflectance function

Where You Are is Who You Are: User Identification by Matching Statistics

Shapes from pixels

VITRAIL : Acquisition, Modelling and Rendering of Stained Glass

The recursive Hessian sketch for adaptive filtering

Sampling and Reconstruction of Shapes with Algebraic Boundaries

SHAPE: Linear-Time Camera Pose Estimation With Quadratic Error-Decay

Learning Network Structures from Firing Patterns

From Acoustic Room Reconstruction to SLAM