Publications related to Shapes from Pixels

A Novel Method for Sampling Bandlimited Graph Signals

Pascal Frossard, Pinar Akyazi, Dion Eustathios Olivier Tzamarias

In this paper we propose a novel vertex based sampling method for k-bandlimited signals lying on arbitrary graphs, that has a reasonable computational complexity and results in low reconstruction error. Our goal is to find the smallest set of vertices that ...

IEEE COMPUTER SOC2018

Sampling at unknown locations: Uniqueness and reconstruction under constraints

Martin Vetterli, Benjamin Bejar Haro, Adam James Scholefield, Golnooshsadat Elhami, Michalina Wanda Pacholska

Traditional sampling results assume that the sample locations are known. Motivated by simultaneous localization and mapping (SLAM) and structure from motion (SfM), we investigate sampling at unknown locations. Without further constraints, the problem is of ...

2018

High Dimensional Bayesian Optimization via Additive Models with Overlapping Groups

Volkan Cevher, Paul Thierry Yves Rolland, Jonathan Mark Scarlett, Ilija Bogunovic

Bayesian optimization (BO) is a popular technique for sequential black-box function optimization, with applications including parameter tuning, robotics, environmental monitoring, and more. One of the most important challenges in BO is the development of a ...

2018

Assessment of water resource contamination by pesticides in vegetable-producing areas in Burkina Faso

Luiz Felippe De Alencastro, Edouard René Gilbert Lehmann, Jean-Jacques Stéphane Nfon Dibie, Morgan Fargues

This study proposes a comprehensive approach to investigate water resource contamination by pesticides under the specific climatic and hydrological conditions of the Sudano-Sahelian climate. Samples were collected from tradi- tional wells, boreholes, and a ...

2018

Impedance-based real-time position sensor for lab-on-a-chip devices

Philippe Renaud, Harald Van Lintel, Jonathan Bastien Cottet

This paper presents the theoretical and experimental development of an integrated position sensor for lab-on-a-chip devices. The interest for single cell analysis is growing. However, this requires monitoring and controlling cell displacements in real time ...

2018

Discrete least-squares approximations over optimized downward closed polynomial spaces in arbitrary dimension

Fabio Nobile, Giovanni Migliorati

We analyze the accuracy of the discrete least-squares approximation of a function

u

in multivariate polynomial spaces

P_\Lambda:=span\{y\mapsto y^\nu \,: \, \nu\in \Lambda\}

with

\Lambda\subset N_0^d

over the domain

\Gamma:=[-1,1]^d

, based on the s ...

2017

Safe Adaptive Importance Sampling

Martin Jaggi, Sebastian Urban Stich, Anant Raj

Importance sampling has become an indispensable strategy to speed up optimization algorithms for large-scale applications. Improved adaptive variants - using importance values defined by the complete gradient information which changes during optimization - ...

2017

Sampling at unknown locations, with an application in surface retrieval

Martin Vetterli, Benjamin Bejar Haro, Adam James Scholefield, Michalina Wanda Pacholska

We consider the problem of sampling at unknown locations. We prove that, in this setting, if we take arbitrarily many samples of a polynomial or real bandlimited signal, it is possible to find another function in the same class, arbitrarily far away from t ...

2017

Sparse Gradient Optimization and its Applications in Image Processing

Nikolaos Arvanitopoulos Darginis

Millions of digital images are captured by imaging devices on a daily basis. The way imaging devices operate follows an integral process from which the information of the original scene needs to be estimated. The estimation is done by inverting the integra ...

EPFL2017

Sampling and Exact Reconstruction of Pulses with Variable Width

Martin Vetterli, Adam James Scholefield, Loïc Arnaud Baboulaz, Gilles Baechler

Recent sampling results enable the reconstruction of signals composed of streams of fixed-shaped pulses. These results have found applications in topics as varied as channel estimation, biomedical imaging and radio astronomy. However, in many real signals, ...

Institute of Electrical and Electronics Engineers2017

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A Novel Method for Sampling Bandlimited Graph Signals

Sampling at unknown locations: Uniqueness and reconstruction under constraints

High Dimensional Bayesian Optimization via Additive Models with Overlapping Groups

Assessment of water resource contamination by pesticides in vegetable-producing areas in Burkina Faso

Impedance-based real-time position sensor for lab-on-a-chip devices

Discrete least-squares approximations over optimized downward closed polynomial spaces in arbitrary dimension

Safe Adaptive Importance Sampling

Sampling at unknown locations, with an application in surface retrieval

Sparse Gradient Optimization and its Applications in Image Processing

Sampling and Exact Reconstruction of Pulses with Variable Width

Sampling at unknown locations: Uniqueness and reconstruction under constraints

A Novel Method for Sampling Bandlimited Graph Signals

Safe Adaptive Importance Sampling

Impedance-based real-time position sensor for lab-on-a-chip devices

Sampling at unknown locations, with an application in surface retrieval

Assessment of water resource contamination by pesticides in vegetable-producing areas in Burkina Faso

Discrete least-squares approximations over optimized downward closed polynomial spaces in arbitrary dimension

Sampling and Exact Reconstruction of Pulses with Variable Width

High Dimensional Bayesian Optimization via Additive Models with Overlapping Groups

Sparse Gradient Optimization and its Applications in Image Processing