Effrosyni Kokiopoulou

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In this paper we discuss the problem of alignment of patterns under arbitrary rotation. When a generic image pattern is geometrically transformed, it typically spans a (possibly nonlinear) manifold in a high dimensional space. When the pattern of interest ...

In the past few years, the problem of distributed consensus has received a lot of attention, particularly in the framework of ad hoc sensor networks. Most methods proposed in the literature address the consensus averaging problem by distributed linear iter ...

Feature extraction based on different types of signal filters has received a lot of attention in the context of face recognition. It generally results into extremely high dimensional feature vectors, and sampling of the coefficients is required to reduce t ...

This paper addresses the problem of image alignment based on random measurements. Image alignment consists of estimating the relative transformation between a query image and a reference image. We consider the specific problem where the query image is prov ...

This paper addresses the problem of representing multimedia information under a compressed form that permits efficient classification. The semantic coding problem starts from a subspace method where dimensionality reduction is formulated as a matrix factor ...

We consider the problem of classification of multiple observations of the same object, possibly under different transformations. We view this problem as a special case of semi-supervised learning where all unlabelled examples belong to the same unknown cla ...

This article explores the feasibility of a market-ready, mo- bile pattern recognition system based on the latest findings in the field of object recognition and currently available hardware and network technology. More precisely, an innovative, mobile muse ...

This paper addresses the problem of 3D face recognition using simultaneous sparse approximations on the sphere. The 3D face point clouds are first aligned with a novel and fully automated registration process. They are then represented as signals on the 2D ...

We consider the problem of distributed average consensus in a sensor network where sensors exchange quantized information with their neighbors. We propose a novel quantization scheme that exploits the increasing correlation between the values exchanged by ...

In the past few years, the problem of distributed consensus has received a lot of attention, particularly in the framework of ad hoc sensor networks. Most methods proposed in the literature attack this problem by distributed linear iterative algorithms, wi ...

Transformation invariance is an important property in pattern recognition, where different observations of the same object typically receive the same label. This paper focuses on a transformation invariant distance measure that represents the minimum dista ...

This paper proposes an algorithm for distributed classification, based on a SVM scheme. The contribution of each support vector is approximated by low complexity distributed thresholding over sub-dictionaries, whose union forms a redundant dictionary of at ...

We consider the problem of distributed classification of multiple observations of the same object that are collected in an ad hoc network of vision sensors. Assuming that each sensor captures a different observation of the same object, the problem is to cl ...

We address the problem of keyword spotting in continuous speech streams when training and testing conditions can be different. We propose a keyword spotting algorithm based on sparse representation of speech signals in a time-frequency feature space. The t ...

We consider the problem of distributed average consensus where sensors exchange quantized data with their neighbors. We deploy a polynomial filtering approach in the network nodes in order to accelerate the convergence of the consensus problem. The quantiz ...

This paper considers the problem of dimensionality reduction by orthogonal projection techniques. The main feature of the proposed techniques is that they attempt to preserve both the intrinsic neighborhood geometry of the data samples and the global geome ...

In this paper, we propose the use of (adaptive) nonlinear approximation for dimensionality reduction. In particular, we propose a dimensionality reduction method for learning a parts based representation of signals using redundant dictionaries. A redundant ...

This paper addresses the problem of 3D face recognition using spherical sparse representations. We first propose a fully automated registration process that permits to align the 3D face point clouds. These point clouds are then represented as signals on th ...

In the past few years, the problem of distributed consensus has received a lot of attention, particularly in the framework of ad hoc sensor networks. Most methods proposed in the literature attack this problem by distributed linear iterative algorithms, wi ...

Effrosyni Kokiopoulou

Chattez avec Graph Search

Image alignment with rotation manifolds built on sparse geometric expansions

Polynomial Filtering for Fast Convergence in Distributed Consensus

Classification-Specific Feature Sampling for Face Recognition

Optimal image alignment with random projections of manifolds: algorithm and geometric analysis

Semantic coding by supervised dimensionality reduction

Graph-based classification of multiple observation sets

Mobile museum guide based on fast SIFT recognition

3D Face Recognition with Sparse Spherical Representations

Distributed average consensus with quantization refinement

Optimal Polynomial Filtering for Accelerating Distributed Consensus

Minimum distance between pattern transformation manifolds: Algorithm and Applications

Distributed SVM applied to image classification

Distributed classification of multiple observation sets by consensus

Fast keyword detection with sparse time-frequency models

Polynomial Filter Design for Quantized Consensus

Orthogonal Neighborhood Preserving Projections: A projection-based dimensionality reduction technique

Dimensionality Reduction with Adaptive Approximation

3D Face Recognition using Sparse Spherical Representations

Accelerating Distributed Consensus Using Extrapolation

An estimator for the diagonal of a matrix