Publications by Elif Vural | EPFL Graph Search

Related publications (19)

Curvature Analysis of Pattern Transformation Manifolds

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

Alignment of uncalibrated images for multi-view classification

Ömer Sercan Arik, Pascal Frossard, Elif Vural

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

Mask Combination of Multi-Layer Graphs for Global Structure Inference

Pascal Frossard, Ntorina Thanou, Elif Vural, Eda Bayram

Structure inference is an important task for network data processing and analysis in data science. In recent years, quite a few approaches have been developed to learn the graph structure underlying a set of observations captured in a data space. Although ...

2020

A graph signal filtering-based approach for detection of different edge types on airborne lidar data

Elif Vural, Eda Bayram

Airborne Laser Scanning is a well-known remote sensing technology, which provides a dense and highly accurate, yet unorganized point cloud of earth surface. During the last decade, extracting information from the data generated by airborne LiDAR systems ha ...

2017

Tangent space estimation for smooth embeddings of Riemannian manifolds

Pascal Frossard, Elif Vural, Hemant Tyagi

Numerous dimensionality reduction problems in data analysis involve the recovery of low-dimensional models or the learning of manifolds underlying sets of data. Many manifold learning methods require the estimation of the tangent space of the manifold at a ...

Oxford University Press2013

Transformation-Invariant Analysis of Visual Signals with Parametric Models

Elif Vural

The analysis of collections of visual data, e.g., their classification, modeling and clustering, has become a problem of high importance in a variety of applications. Meanwhile, image data captured in uncontrolled environments by arbitrary users is very li ...

EPFL2013

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-Invariant Dictionary Learning for Classification with 1-Sparse Representations

Pascal Frossard, Elif Vural, Ahmet Caner Yüzügüler

Sparse representations of images in well-designed dictionaries can be used for effective classification. Meanwhile, training data available in most realistic settings are likely to be exposed to geometric transformations, which poses a challenge for the de ...

2014

Learning Smooth Pattern Transformation Manifolds

Pascal Frossard, Elif Vural

Manifold models provide low-dimensional representations that are useful for processing and analyzing data in a transformation-invariant way. In this paper, we study the problem of learning smooth pattern transformation manifolds from image sets that are ob ...

Institute of Electrical and Electronics Engineers2013

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

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

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

Analysis of Descent-Based Image Registration

Pascal Frossard, Elif Vural

We present a performance analysis for image registration with gradient descent. We consider a typical multiscale registration setting where the global 2-D translation between a pair of images is estimated by smoothing the images and minimizing the distance ...

2013

Analysis of Image Registration with Tangent Distance

Pascal Frossard, Elif Vural

The computation of the geometric transformation between a reference and a target image, known as image registration or alignment, corresponds to the projection of the target image onto the transformation manifold of the reference image (the set of images g ...

2014

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

Elif Vural

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Curvature Analysis of Pattern Transformation Manifolds

Alignment of uncalibrated images for multi-view classification

Mask Combination of Multi-Layer Graphs for Global Structure Inference

A graph signal filtering-based approach for detection of different edge types on airborne lidar data

Tangent space estimation for smooth embeddings of Riemannian manifolds

Transformation-Invariant Analysis of Visual Signals with Parametric Models

Distance-Based Discretization of Parametric Signal Manifolds

Transformation-Invariant Dictionary Learning for Classification with 1-Sparse Representations

Learning Smooth Pattern Transformation Manifolds

Learning Pattern Transformation Manifolds for Classification

Discretization of Parametrizable Signal Manifolds

Learning pattern transformation manifolds with parametric atom selection

Analysis of Descent-Based Image Registration

Analysis of Image Registration with Tangent Distance

Approximation of Pattern Transformation Manifolds with Parametric Dictionaries

A Performance Study of the Tangent Distance Method in Transformation-Invariant Image Classification

Tangent Space Estimation Bounds for Smooth Manifolds

Analysis of Hierarchical Image Alignment with Descent Methods

Analysis of Airborne LiDAR Point Clouds with Spectral Graph Filtering