Person

Elif Vural

This person is no longer with EPFL

Related publications (17)

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Learning Pattern Transformation Manifolds for Classification

Pascal Frossard, Elif Vural

Manifold models provide low-dimensional representations that are useful for analyzing and classifying data in a transformation-invariant way. In this paper we study the problem of jointly building multiple pattern transformation manifolds from a collection ...

2012

Alignment of uncalibrated images for multi-view classification

Pascal Frossard, Elif Vural, Ömer Sercan Arik

Efficient solutions for the classification of multi-view images can be built on graph-based algorithms when little information is known about the scene or cameras. Such methods typically require a pairwise similarity measure between images, where a common ...

2011

Approximation of Pattern Transformation Manifolds with Parametric Dictionaries

Pascal Frossard, Elif Vural

The construction of low-dimensional models explaining high-dimensional signal observations provides concise and efficient data representations. In this paper, we focus on pattern transformation manifold models generated by in-plane geometric transformation ...

2011

Learning pattern transformation manifolds with parametric atom selection

Pascal Frossard, Elif Vural

We address the problem of building a manifold in order to represent a set of geometrically transformed images by selecting a good common sparse approximation of them with parametric atoms. We propose a greedy method to construct a representative pattern su ...

2011

Discretization of Parametrizable Signal Manifolds

Pascal Frossard, Elif Vural

Transformation-invariant analysis of signals often requires the computation of the distance from a test pattern to a transformation manifold. In particular, the estimation of the distances between a transformed query signal and several transformation manif ...

Institute of Electrical and Electronics Engineers2011

Distance-Based Discretization of Parametric Signal Manifolds

Pascal Frossard, Elif Vural

The characterization of signals and images in manifolds often lead to efficient dimensionality reduction algorithms based on manifold distance computation for analysis or classification tasks. We propose in this paper a method for the discretization of sig ...

2010

Transformation manifolds are quite attractive for image analysis applications that require transformation invariance properties. The geometric structure of a transformation manifold has a profound influence on the design of processing algorithm, and the cu ...

2010