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Target tracking using a joint acoustic video system

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A Multiple Hypothesis Gaussian Mixture Filter for Acoustic Source Localization and Tracking

In this work, we address the problem of tracking an acoustic source based on measured time differences of arrival (TDOA). The classical solution to this problem consists in using a detector, which estimates the TDOA for each microphone pair, and then apply ...

2012

Model-Based Similarity Measure in TimeCloud

Karl Aberer, Ho Young Jeung

This paper presents a new approach to measuring similarity over massive time-series data. Our approach is built on two principles: one is to parallelize the large amount computation using a scalable cloud serving system, called TimeCloud. The another is to ...

Springer2012

A Wideband Doubly-Sparse Approach For MITO Sparse Filter Estimation

Rémi Gribonval

We propose an approach for the estimation of sparse filters from a convolutive mixture of sources, exploiting the time-domain sparsity of the mixing filters and the sparsity of the sources in the time-frequency (TF) domain. The proposed approach is based o ...

IEEE2011

Filter Learning for Linear Structure Segmentation

Pascal Fua, Engin Türetken, Vincent Lepetit, Germán González Serrano, Roberto Rigamonti

We introduce an approach to learning convolution filters whose joint output can be fed to a classifier that labels them as belonging to linear structures or not. The filters are learned using sparse synthesis techniques but we show that enforcing constrain ...

2011

Kalman Filter to Measure Position and Speed of a Linear Actuator

Yves Perriard, Miroslav Markovic, Joël Maridor

This paper presents a method to dynamically filter the position and the speed of a linear actuator during its closing. A previous paper presented position detection without external sensor but, by simply deriving it, the corresponding speed was not usable ...

IEEE2011

Double Sparsity: Towards Blind Estimation of Multiple Channels

Rémi Gribonval

We propose a framework for blind multiple filter estimation from convolutive mixtures, exploiting the time-domain sparsity of the mixing filters and the disjointness of the sources in the time-frequency domain. The proposed framework includes two steps: (a ...

Springer-Verlag's2010

Diffusion Strategies for Distributed Kalman Filtering and Smoothing

Ali H. Sayed

We study the problem of distributed Kalman filtering and smoothing, where a set of nodes is required to estimate the state of a linear dynamic system from in a collaborative manner. Our focus is on diffusion strategies, where nodes communicate with their d ...

IEEE2010

Grid Filter Modeling for Large-Eddy Simulation

Michel Deville, Marc Anthony David Habisreutinger, Roland Bouffanais

An interpretation to the use of deconvolution models when used in implicitly filtered large-eddy simulations as a way to approximate the projective grid filter is given. Consequently, a new category of subgrid models, the grid filter models, is defined. Th ...

Springer-Verlag New York, Ms Ingrid Cunningham, 175 Fifth Ave, New York, Ny 10010 Usa2010

UMTS-WiFi Switchable Bandpass Filter

Julien Perruisseau-Carrier

In this paper a reconfigurable bandpass filter able to switch between WiFi and UMTS transmit band standards is presented. The filter is designed in such a way that center frequency and bandwidth specifications are precisely met by defining a switchable fil ...

2009

Video-Based Camera Tracking Using Rotation-Discriminative Template Matching

Touradj Ebrahimi

This paper presents a video-based camera tracker that combines marker-based and feature point-based cues in a particle filter framework. The framework relies on their complementary performance. Marker-based trackers can robustly recover camera position and ...

Springer2009