Publications by Pascal Frossard

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This work addresses the modeling of traffic generated by a video source operating in the context of adaptive streaming services. Traffic modeling is a key in several network design issues, such as dimensioning of core and access network resources, developi ...

Full immersion inside a Virtual Reality (VR) scene requires six Degrees of Freedom (6DoF) applications where the user is allowed to perform translational and rotational movements within the virtual space. The implementation of 6DoF applications is however ...

We propose an approach for estimating graph diffusion processes using annihilation filters from a finite set of observations of the diffusion process made at regular intervals. Our approach is based on the key observation that a graph diffusion process can ...

This paper addresses the reconstruction of high resolution omnidirectional images from multiple low resolution images with inexact registration. When omnidirectional images from low resolution vision sensors can be uniquely mapped on the 2-sphere, such a reconstruction can be described as a transform domain super-resolution problem in the spherical imaging framework. We describe how several spherical images with arbitrary rotations in the SO(3) rotation group contribute to the reconstruction of a high resol

This paper addresses the problem of compact representation of a 3D scene, captured by distributed omnidirectional cameras. As the images from the sensors are likely to be correlated in most practical scenarios, we build a distributed algorithm based on cod ...

In this paper we address the problem of learning image structures directly from sparse codes. We first model images as linear combinations of molecules, which are themselves groups of atoms from a redundant dictionary. We then formulate a new structure lea ...

We present a performance analysis for image registration with gradient descent methods. 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 between them with gradient descent. Our study particularly concentrates on the effect of noise and low-pass filtering on the alignment accuracy. We adopt an analytic representation for images and analyze the well-behavedness of the image distance

Orthogonal frequency-division multiplexing (OFDM) is widely used to mitigate inter-symbol interference (ISI) from multipath fading. However, the open nature of wireless OFDM systems makes them vulnerable to jamming attacks. In this context, pilot jamming i ...

This paper addresses the problem of correlation estimation in sets of compressed images. We consider a framework where images are represented under the form of linear measurements due to low complexity sensing or security requirements. We assume that the i ...

Clustering on graphs has been studied extensively for years due to its numerous applications. However, in contrast to the classic problems, clustering in mobile and online social networks brings new challenges. In these scenarios, it is common that observational data contains multiple modalities of information reflecting different aspects of human behavior and social interactions. These interactions may be represented by a multi-layer graph that share the same set of vertices representing users, while havin

We address the problem of joint path selection and rate allocation in multipath wireless streaming, in order to optimize a media specific quality of service. We leverage on the existence of multiple parallel wireless services, in order to enhance the recei ...

This paper presents a novel rate allocation scheme to compute the 3D structure of the scene from compressed stereo images, captured by the distributed vision sensor networks. The images captured at different view points are encoded independently with a bal ...

This paper introduces an algorithm for sparse approximation in redundant dictionaries, called the M-Term Pursuit (MTP), based on the matching pursuit approach (MP). This algorithm decomposes the signal into a linear combination of selected atoms, chosen to represent the signal components. The MTP algorithm provides adaptive representation for signals in any dictionary. The basic idea behind the MTP, is to partition the dictionary into

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disjoint sub-dictionaries, each carrying some meaningful information.

We address the problem of joint path selection and video source rate allocation in multipath streaming in order to optimize a media specific quality of service. An optimization problem is proposed, which aims at minimizing a video distortion metric based o ...

Multiview video with interactive and smooth view switching at the receiver is a challenging application with several issues in terms of effective use of storage and bandwidth resources, reactivity of the system, quality of the viewing experience and system ...

This paper presents a distributed coding scheme for the representation of 3D scenes captured by omnidirectional cameras. We consider a scenario with a pair of similar cameras that benefit from equivalent bandwidth and computational resources. The images are captured at different viewpoints and encoded independently, while a joint decoder exploits the correlation between images for improved decoding quality. The distributed coding is built on the multiresolution representation of spherical images, whose info

We address the problem of prioritized video streaming over lossy overlay networks. We propose to exploit network path diversity via a novel Randomized Network Coding (RNC) approach that provides unequal error protection (UEP) to the packets conveying the video content. We design a distributed receiver-driven streaming solution, where a client requests packets from the different priority classes from its neighbours in the overlay. Based on received requests, a node in turn forwards combinations of packets fr

Sparsity has been one of the major drives in signal processing in the last decade. Structured sparsity has also lately emerged as a way to enrich signal priors towards more meaningful and accurate representations. In this paper we propose a new structured ...

Additive models are regression methods which model the response variable as the sum of univariate transfer functions of the input variables. Key benefits of additive models are their accuracy and interpretability on many real-world tasks. Additive models a ...

We consider the problem of distributed packet selection and scheduling for multiple video streams sharing a communication channel. An optimization framework is proposed, that enables the multiple senders to coordinate their packet transmission schedules, s ...

Pascal Frossard

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Joint Source and Transmission Rate Modeling in Adaptive Video Streaming

Dynamic Adaptive Streaming for Multi-Viewpoint Omnidirectional Videos

Annihilation Filter Approach For Estimating Graph Dynamics From Diffusion Processes

Joint registration and super-resolution with omnidirectional images

Distributed coding of multiresolution omnidirectional images

Learning from sparse codes

Analysis of Descent-Based Image Registration

Adversarial Training for Jamming-Robust Channel Estimation in OFDM Systems

Correlation Estimation from Compressed Images

Methods for Clustering Multi-Layer Graphs in Mobile Networks

Media-specific rate allocation in heterogeneous wireless networks

Bit Rate Allocation for Disparity Estimation from Compressed Images

Sparse Approximation Using M-Term Pursuits with Applications to Image and Video Compression

Media Flow Rate Allocation in Multipath Networks

Interactive Multiview Video System With Low Complexity 2D Look Around at Decoder

Symmetric Distributed Coding of Stereo Omnidirectional Images

Prioritized Distributed Video Delivery with Randomized Network Coding

Structured Sparse Coding for Image Denoising or Pattern Detection

Structured Dimensionality Reduction for Additive Model Regression

Rate-Distortion Optimized Distributed Packet Scheduling of Multiple Video Streams over Shared Communication Resources