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Feature point tracking combining the Interacting Multiple Model filter and an efficient assignment algorithm

Related publications (52)

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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

An Adaptive Diffusion Augmented CLMS Algorithm for Distributed Filtering of Noncircular Complex Signals

Ali H. Sayed

An adaptive diffusion augmented complex least mean square (D-ACLMS) algorithm for collaborative processing of the generality of complex signals over distributed networks is proposed. The algorithm enables the estimation of both second order circular (prope ...

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

Distributed nonlinear Kalman filtering with applications to wireless localization

Ali H. Sayed

We study the problem of distributed state-space estimation, where a set of nodes are required to estimate the state of a nonlinear state-space system based on their observations. We extend our previous work on distributed Kalman filtering to the nonlinear ...

IEEE2010

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

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

Adaptive frequency tracking and application to biomedical signals

Yann Prudat

The main information of a signal resides in its frequency, its amplitude (or its power) and in their temporal evolution. Thus, a great number of methods for instantaneous frequency estimation have been proposed in the literature. Most of these algorithms u ...

EPFL2009

Diffusion recursive least-squares for distributed estimation over adaptive networks

Ali H. Sayed

We study the problem of distributed estimation over adaptive networks where a collection of nodes are required to estimate in a collaborative manner some parameter of interest from their measurements. The centralized solution to the problem uses a fusion c ...

Institute of Electrical and Electronics Engineers2008