Publications de Pascal Frossard

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This paper addresses the problem of mapping images between different vision sensors. Such a mapping could be modeled as a sampling problem that has to encompass the change of geometry between the two sensors and the specific discretization of the real scen ...

A depth image provides partial geometric information of a 3D scene, namely the shapes of physical objects as observed from a particular viewpoint. This information is important when synthesizing images of different virtual camera viewpoints via depth-image ...

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 ...

In free viewpoint video, a viewer can choose at will any camera angle or the so-called "virtual view" to observe a dynamic 3-D scene, enhancing his/her depth perception. The virtual view is synthesized using texture and depth videos of two anchor camera vi ...

We consider the problem of distributed average consensus in a sensor network where sensors exchange quantized information with their neighbors. In particular, we exploit the increasing correlation between the exchanged values throughout the iterations of t ...

Network coding permits to deploy distributed packet delivery algorithms that locally adapt to the network availability in media streaming applications. However, it may also increase delay and computational complexity if it is not implemented efficiently. W ...

Classifiers based on sparse representations have recently been shown to provide excellent results in many visual recognition and classification tasks. However, the high cost of computing sparse representations at test time is a major obstacle that limits t ...

We consider the problem of failure detection in sensor networks and we propose a new distributed detection algorithm based on Group Testing. We examine the presence of defective sensors by employing tests over locally gathered sensor measurements. Tests ar ...

We consider the problem of inferring the hidden structure of high-dimensional dynamic systems from the perspective of graph learning. In particular, we aim at capturing the dynamic relationships between nodes by a sequence of graphs. Our approach is motiva ...

Sparsity-based models have proven to be very effective in most image processing applications. The notion of sparsity has recently been extended to structured sparsity models where not only the number of components but also their support is important. This ...

This paper considers a framework where data from correlated sources are transmitted with help of network coding in ad-hoc network topologies. The correlated data are encoded independently at sensors and network coding is employed in the intermediate nodes ...

In Virtual Reality (VR) applications, understanding how users explore the omnidirectional content is important to optimize content creation, to develop user-centric services, or even to detect disorders in medical applications. Clustering users based on th ...

This paper introduces a novel algorithm for sparse approximation in redundant dictionaries called the M-term pursuit (MTP). This algorithm decomposes a signal into a linear combination of atoms that are selected in order to represent the main signal compon ...

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 work addresses the optimization of TV-resolution MPEG-2 video streams to be transmitted over lossy packet networks. This paper introduces a new scene-complexity adaptive mechanism, namely the Adaptive MPEG-2 Information Structuring (AMIS) mechanism. AMIS adaptively modulates the number of resynchronization points (i.e the slice headers and intra-coded macroblocks) in order to maximize the perceived video quality assuming it is aware of the packet loss probability and the error concealment technique imp

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 ...

The effective representation, processing, analysis, and visualization of large-scale structured data, especially those related to complex domains, such as networks and graphs, are one of the key questions in modern machine learning. Graph signal processing ...

Blood pressure (BP) is a crucial biomarker giving valuable information regarding cardiovascular diseases but requires accurate continuous monitoring to maximize its value. In the effort of developing non-invasive, non-occlusive and continuous BP monitoring ...

We propose a method for learning dictionaries towards sparse approximation of signals defined on vertices of arbitrary graphs. Dictionaries are expected to describe effectively the main spatial and spectral components of the signals of interest, so that th ...

Depth image based rendering techniques for multiview applications have been recently introduced for efficient view generation at arbitrary camera positions. Encoding rate control has thus to consider both texture and depth data. Due to different structures ...

Pascal Frossard

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TV-Regularized Generation of Planar Images from Omnicams

Object Shape Approximation and Contour Adaptive Depth Image Coding for Virtual View Synthesis

Learning Pattern Transformation Manifolds for Classification

Anchor View Allocation for Collaborative Free Viewpoint Video Streaming

Progressive quantization in distributed average consensus

Selection of Network Coding Nodes for Minimal Playback Delay in Streaming Overlays

Dictionary learning for fast classification based on soft-thresholding

Distributed Group Testing Detection in Sensor Networks

Learning time varying graphs

Sparse molecular image representation

Approximate Decoding Approaches for Network Coded Correlated Data

Spherical Clustering of Users Navigating 360° Content

Sparse Approximation Using M-Term Pursuit and Application in Image and Video Coding

Minimum distance between pattern transformation manifolds: Algorithm and Applications

Adaptive MPEG-2 Information Structuring

Distributed SVM applied to image classification

Graph Signal Processing for Machine Learning: A Review and New Perspectives

Blood pressure monitoring during anesthesia induction using PPG morphology features and machine learning

Learning of Structured Graph Dictionaries

Rate-distortion analysis of multiview coding in a DIBR framework