Pierre Vandergheynst

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This paper discusses robust coding of visual content for a distributed multimedia system. The system encodes independently two correlated video signals and reconstructs them jointly at a central decoder. The video signals are captured from a dynamic scene ...

We propose a simple and efficient technique for designing translation invariant dyadic wavelet transforms (DWTs) in two dimensions. Our technique relies on an extension of the work of Duval-Destin et al. (1993) where dyadic decompositions are constructed starting from the continuous wavelet transform. The main advantage of this framework is that it allows for a lot of freedom in designing two-dimensional (2-D) dyadic wavelets. We use this property to construct directional wavelets, whose orientation filteri

We discuss a novel sampling theorem on the sphere developed by McEwen & Wiaux recently through an association between the sphere and the torus. To represent a band-limited signal exactly, this new sampling theorem requires less than half the number of samp ...

We study the problem of sampling k-bandlimited signals on graphs. We propose two sampling strategies that consist in selecting a small subset of nodes at random. The first strategy is non-adaptive, i.e., independent of the graph structure, and its performa ...

The analysis of oriented features in images requires two-dimensional directional wavelets. Among these, we study in detail the class of Cauchy wavelets, which are strictly supported in a (narrow) convex cone in spatial frequency space. They have excellent angular selectivity, as shown by a standard calibration test, and they have minimal uncertainty. In addition, we present a new application of directional wavelets, namely a technique for determining the symmetries of a given pattern with respect to rotatio

Standard image sensors feature dynamic range about 60 to 70 dB while the light flux of natural scenes may be over 120 dB. Most imagers dedicated to address such dynamic ranges, need specific, and large pixels. However, canonical imagers can be used for hig ...

We review scale-discretized wavelets on the sphere, which are directional and allow one to probe oriented struc- ture in data defined on the sphere. Furthermore, scale-discretized wavelets allow in practice the exact synthesis of a signal from its wavelet ...

We consider the problem of reconstruction of astrophysical signals probed by radio interferometers with baselines bearing a non-negligible component in the pointing direction. The visibilities measured essentially identify with a noisy and incomplete Fouri ...

In this paper the Continuous Wavelet Transform on the sphere is exploited to build the asociated Discrete Wavelet Frames. First, the half-continuous frames, i.e. frames where the position remains a continuous variable, is presented and then the fully discrete theory is presented. The notion of controlled frames is introduced, which reflects the particular nature of the underlying theory, particularly the apperant conflict between dilation and the compacity of the sphere. The paper is concluded with some num

A novel approach is presented to locate dense crowd of people in a network of fixed cameras given the severely degraded background subtracted silhouettes. The problem is formulated as a sparsity constrained inverse problem using an adaptive dictionary constructed on- line. The framework has no constraint on the number of cameras neither on the surface to be monitored. Even with a single camera, partially occluded and grouped people are correctly detected and segmented. Qualitative results are presented in i

In this work, we explore a framework for the sparse representation of video sequences by means of spatio

In this paper we build a Continuous Wavelet Transform (CWT) on the upper sheet of the 2-hyperboloid

H_+^2

. First, we define a class of suitable dilations on the hyperboloid through conic projection. Then, incorporating hyperbolic motions belonging to $SO ...

This article presents an alteration of greedy algorithms like thresholding or (Orthogonal) Matching Pursuit which improves their performance in finding sparse signal representations in redundant dictionaries. These algorithms can be split into a sensing an ...

A method to create a video sequence of a plurality of resultant images is disclosed. The video sequence is produced from images originating from a rolling shutter acquisition sensor. ...

Vision-based background subtraction algorithms model the intensity variation across time to classify a pixel as foreground. Unfortunately, such algorithms are sensitive to appearance changes of the background such as sudden changes of illumination or when ...

This paper presents a methodology for extracting meaningful synchronous structures from multi-modal signals. Simultaneous processing of multi-modal data can reveal information that is unavailable when handling the sources separately. However, in natural hi ...

We propose a new multiscale image segmentation model, based on the active contour/snake model and the Polyakov action. The concept of scale, general issue in physics and signal processing, is introduced in the active contour model, which is a well-known im ...

The active contour/snake model is one of the most successful variational models in image segmentation. It consists of evolving a contour in images toward the boundaries of objects. Its success is based on strong mathematical properties and efficient numeri ...

A sampling theorem on the sphere has been developed recently, requiring half as many samples as alternative equiangular sampling theorems on the sphere. A reduction by a factor of two in the number of samples required to represent a band-limited signal on ...

De novo protein design explores uncharted sequence and structure space to generate novel proteins not sampled by evolution. A main challenge in de novo design involves crafting “designable” structural templates to guide the sequence searches toward adoptin ...

Pierre Vandergheynst

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Distributed coding of Highly correlated image sequences with motion-compensated temporal wavelets

Directional dyadic wavelet transforms: design and algorithms

Sampling theorems and compressive sensing on the sphere

Random sampling of bandlimited signals on graphs

Directional Wavelets Revisited: Cauchy Wavelets and Symmetry Detection in Patterns

An Algorithm Architecture Co-Design for CMOS Compressive High Dynamic Range Imaging

On the computation of directional scale-discretized wavelet transforms on the sphere

Compressed sensing for radio interferometry: spread spectrum imaging techniques

Discrete Wavelet Frames on the Sphere

A Sparsity Constrained Inverse Problem to Locate People in a Network of Cameras

A Bayesian Approach to Video Expansions on Parametric Over-Complete 2-D Dictionaries

Continuous Wavelet Transform on the Hyperboloid

Dictionary preconditioning for greedy algorithms

Method to compensate the effect of the rolling shutter effect

Foreground Silhouette Extraction robust to Sudden Changes of background Appearance

Learning Multi-Modal Dictionaries: Application to Audiovisual Data

Multiscale Active Contours

Fast Global Minimization of the Active Contour/Snake Model

Implications for compressed sensing of a new sampling theorem on the sphere

Exploring “dark-matter” protein folds using deep learning