Publications related to Motion likelihood and proposal modeling in Model-Based Stochastic Tracking

PoGaIN: Poisson-Gaussian Image Noise Modeling From Paired Samples

Sabine Süsstrunk, Majed El Helou, Kaan Okumus

Image noise can often be accurately fitted to a Poisson-Gaussian distribution. However, estimating the distribution parameters from a noisy image only is a challenging task. Here, we study the case when paired noisy and noise-free samples are accessible. N ...

2022

An Efficient Signal-to-noise Approximation for Eccentric Inspiraling Binaries

Alexandra Shelest

Eccentricity has emerged as a potentially useful tool for helping to identify the origin of black hole mergers. However, eccentric templates can be computationally very expensive owing to the large number of harmonics, making statistical analyses to distin ...

IOP Publishing Ltd2022

Weakly-supervised Action Transition Learning for Stochastic Human Motion Prediction

Mathieu Salzmann, Wei Mao

We introduce the task of action-driven stochastic human motion prediction, which aims to predict multiple plausible future motions given a sequence of action labels and a short motion history. This differs from existing works, which predict motions that ei ...

IEEE COMPUTER SOC2022

Sensitivity, Noise and Resolution in a B -Modified Foundry-Made ISFET with Miniaturized Reference Electrode for Wearable Point-of-Care Applications

Mihai Adrian Ionescu, Junrui Zhang, Francesco Bellando, Pierpaolo Palestri, Luca Selmi

Ion-sensitive field-effect transistors (ISFETs) form a high sensitivity and scalable class of sensors, compatible with advanced complementary metal-oxide semiconductor (CMOS) processes. Despite many previous demonstrations about their merits as low-power ...

2021

How does one compute the noise power to simulate real and complex GNSS signals?

Cyril Botteron, Jérôme Leclère

Simulation of GNSS signals is very important to test and validate algorithms. With some algorithms, such as acquisition or tracking, we do not need to simulate a realistic constellation with actual ranges, Doppler or navigation data. We can simply simulate ...

2016

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

A consensus algorithm for networks with process noise and quantization error

Colin Neil Jones, Ye Pu, Andrea Alessandretti, Francisco Fernandes Castro Rego

In this paper we address the problem of quantized consensus where process noise or external inputs corrupt the state of each agent at each iteration. We propose a quantized consensus algorithm with progressive quantization, where the quantization interval ...

IEEE2015

Convergence estimates in probability and in expectation for discrete least squares with noisy evaluations at random points

Fabio Nobile, Giovanni Migliorati

We study the accuracy of the discrete least-squares approximation on a finite-dimensional space of a real-valued target function from noisy pointwise evaluations at independent random points distributed according to a given sampling probability measure. Th ...

2015

MATHICSE Technical Report : Convergence estimates in probability and in expectation for discrete least squares with noisy evaluations at random points

Fabio Nobile, Giovanni Migliorati

We study the accuracy of the discrete least-squares approximation on a finite dimensional space of a real-valued target function from noisy pointwise evaluations at independent random points distributed according to a given sampling probability measure. Th ...

MATHICSE2015

Robust Microphone Placement for Source Localization from Noisy Distance Measurements

Hervé Bourlard, Philip Neil Garner, Afsaneh Asaei, Mohammadjavad Taghizadeh, Saeid Haghighatshoar

We propose a novel algorithm to design an optimum array geometry for source localization inside an enclosure. We assume a square-law decay propagation model for the sound acquisition so that the additive noise on the measured source-microphone distances is ...

2015

Motion likelihood and proposal modeling in Model-Based Stochastic Tracking

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PoGaIN: Poisson-Gaussian Image Noise Modeling From Paired Samples

An Efficient Signal-to-noise Approximation for Eccentric Inspiraling Binaries

Weakly-supervised Action Transition Learning for Stochastic Human Motion Prediction

Sensitivity, Noise and Resolution in a B -Modified Foundry-Made ISFET with Miniaturized Reference Electrode for Wearable Point-of-Care Applications

How does one compute the noise power to simulate real and complex GNSS signals?

Sampling and Reconstruction of Shapes with Algebraic Boundaries

A consensus algorithm for networks with process noise and quantization error

Convergence estimates in probability and in expectation for discrete least squares with noisy evaluations at random points

MATHICSE Technical Report : Convergence estimates in probability and in expectation for discrete least squares with noisy evaluations at random points

Robust Microphone Placement for Source Localization from Noisy Distance Measurements

An Efficient Signal-to-noise Approximation for Eccentric Inspiraling Binaries

Sensitivity, Noise and Resolution in a B -Modified Foundry-Made ISFET with Miniaturized Reference Electrode for Wearable Point-of-Care Applications

Weakly-supervised Action Transition Learning for Stochastic Human Motion Prediction

How does one compute the noise power to simulate real and complex GNSS signals?

MATHICSE Technical Report : Convergence estimates in probability and in expectation for discrete least squares with noisy evaluations at random points

A consensus algorithm for networks with process noise and quantization error

Convergence estimates in probability and in expectation for discrete least squares with noisy evaluations at random points

Robust Microphone Placement for Source Localization from Noisy Distance Measurements

PoGaIN: Poisson-Gaussian Image Noise Modeling From Paired Samples

Sampling and Reconstruction of Shapes with Algebraic Boundaries