Publications de Pascal Frossard

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This paper presents a distortion optimized streaming algorithm for on-demand streaming of multimedia. Given the pre-encoded packets of a multimedia stream, we propose an algorithm for selecting an appropriate subset of these packets such that the overall client distortion is minimized. This minimization is performed within the rate constraints imposed by the communication channel. In the interest of computation it is desirable to limit the horizon (i.e. the look-ahead) over which the optimization is perform

This paper presents a progressive coding scheme for 3-D objects, based on overcomplete signal expansions on the 2-D sphere. Due to increased freedom in the basis construction, redundant expansions have shown interesting approximation properties in the deco ...

In this paper, we propose an algorithm to detect a specific kind of distortions, referred to as seams, which commonly occur when a 360-degree image is represented in planar domain by projecting the sphere to a polyhedron, e.g, via the Cube Map (CM) project ...

In this paper, we address the design of any number of balanced descriptions using multiple description scalar quantization (MDSQ), based on fast index assignment. The proposed scheme has the advantages of low complexity, and the possibility of being extended easily to any number of descriptions. Unlike existing schemes, it can produce balanced descriptions even at low rate, at the price however of a slightly higher distortion. The behavior of the proposed index assignment at high rate is in the same time si

In this paper, we propose a representation selection optimization problem for complexity constrained adaptive video streaming that properly takes into account the different complexity-rate-distortion (C-R-D) characteristics of the videos when implementing ...

This paper addresses the problem of the interpolation of 2-d spherical signals from non-uniformly sampled and noisy data. We propose a graph-based regularization algorithm to improve the signal reconstructed by local interpolation methods such as nearest n ...

Color plus depth format allows building 3D representations of scenes within which the users can freely navigate by changing their viewpoints. In this paper we present a framework for view synthesis when the user requests an arbitrary viewpoint that is clos ...

Observational data usually comes with a multimodal nature, which means that it can be naturally represented by a multi-layer graph whose layers share the same set of vertices (users) with different edges (pairwise relationships). In this paper, we address ...

Deep Neural Networks are being extensively used in communication systems and Automatic Modulation Classification (AMC) in particular. However, they are very susceptible to small adversarial perturbations that are carefully crafted to change the network decision. In this work, we build on knowledge distillation ideas and adversarial training in order to build more robust AMC systems. We first outline the importance of the quality of the training data in terms of accuracy and robustness of the model. We then

Blood pressure (BP) is an important indicator for prevention and management of cardiovascular diseases. Alongside the improvement in sensors and wearables, photoplethysmography (PPG) appears to be a promising technology for continuous, non-invasive and cuf ...

In this paper, we propose a new representation for multiview image sets. Our approach relies on graphs to describe geometry information in a compact and controllable way. The links of the graph connect pixels in different images and describe the proximity ...

Visual distortions in processed 360-degree visual content and consumed through head-mounted displays (HMDs) are perceived very differently when compared to traditional 2D content. To better understand how compression-related artifacts affect the overall pe ...

Developing effective 360-degree (spherical) image compression techniques is crucial for technologies like virtual reality and automated driving. This paper advances the state-of-the-art in on-the-sphere learning (OSLO) for omnidirectional image compression ...

In this paper, the performances of packet-level media-independent FEC schemes are computed in terms of both packet loss ratio and average burst length of multimedia data after error recovery. The set of equations leading to the analytical formulation of both parameters are first given for a renewal error process. Finally, the FEC performances parameters are computed in the case of a Gilbert-model loss process and compared to experimental data.

Recently, it has been shown that, in spite of the significant performance of deep neural networks in different fields, those are vulnerable to adversarial examples. In this paper, we propose a gradient-based adversarial attack against transformer-based tex ...

In sparse signal representation, the choice of a dictionary often involves a tradeoff between two desirable properties – the ability to adapt to specific signal data and a fast implementation of the dictionary. To sparsely represent signals residing on wei ...

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 ...

We address the problem of distributed path selection and rate allocation for media streaming in overlay networks. Under the assumption that each node has only a local view of the network, we propose a distributed algorithm for joint path selection, and rate allocation, in order to minimize the end-to-end media distortion. The distributed algorithm performs iteratively, by greedy rate allocation for all incoming media flows on the outgoing links at each intermediate node. Our algorithm is shown to converge t

The real-time estimation through vision of the physical properties of objects manipulated by humans is important to inform the control of robots for performing accurate and safe grasps of objects handed over by humans. However, estimating the 3D pose and d ...

This chapter discusses the problem of coding images using very redundant libraries of waveforms, also referred to as dictionaries. We start with a discussion of the shortcomings of classical approaches based on orthonormal bases. More specifically, we show why these redundant dictionaries provide an interesting alternative for image representation. We then introduce a special dictionary of 2-D primitives called anisotropic refinement atoms that are well suited for representing edge dominated images. Using a

Pascal Frossard

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Distortion-Buffer Optimized TCP Video Streaming

Progressive Coding of 3-D Objects Based on Overcomplete Decompositions

Graph-Based Detection of Seams In 360-Degree Images

Fast Index Assignment for balanced N-Description Scalar Quantization

Complexity Constrained Representation Selection for Dynamic Adaptive Streaming

Graph-based regularization for spherical signal interpolation

Graph-Based Inpainting of Disocclusion Holes for Zooming in 3D Scenes

Clustering with Multi-Layer Graphs: A Spectral Perspective

Maximum Likelihood Distillation for Robust Modulation Classification

Feature Learning for Blood Pressure Estimation from Photoplethysmography

Graph-based representation for multiview image geometry

Subjective and Viewport-based Objective Quality Assessment of 360-degree Videos

OSLO-IC: On-the-Sphere Learned Omnidirectional Image Compression with Attention Modules and Spatial Context

FEC Performances in Multimedia Streaming

Block-Sparse Adversarial Attack To Fool Transformer-Based Text Classifiers

Learning Parametric Dictionaries for Signals on Graphs

Discretization of Parametrizable Signal Manifolds

Distributed Media Rate Allocation in Overlay Networks

Benchmark for Human-to-Robot Handovers of Unseen Containers with Unknown Filling

Image coding using redundant dictionaries