Publications de Pascal Frossard

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This paper addresses the problem of distributed coding of light fields in camera networks. A novel distributed coding scheme with side information is presented, based on spherical image expansion over an overcomplete dictionary of geometric atoms. We propo ...

Novel network architectures such as overlay networks offer significant diversity that can compensate for the lack of strict quality of service in today's communication infrastructures. In order to take advantage of this diversity for delay-sensitive media streaming applications, the network systems can employ efficient mechanisms based on source, channel and even network coding. In particular, fountain codes offer interesting benefits for streaming with server diversity. When they are used independently at

Non–ST-elevation acute coronary syndrome (NSTE-ACS) remains a diagnostic challenge, as a proportion of patients do not present with obstructive coronary lesions. Coronary computed tomography angiography (CCTA) has emerged as a non-invasive tool for coronary assessment, and integrating artificial intelligence (AI) may enhance its diagnostic accuracy. This study evaluates a machine learning (ML) model using a learned fusion approach to identify culprit lesions in high-risk NSTE-ACS patients. This study is a s

Interactive multiview video streaming (IMVS) services permit to remotely navigate within a 3D scene with an immersive experience. This is possible by transmitting a set of reference camera views (anchor views), which are used by the clients to freely navig ...

This paper proposes a tree-based pursuit algorithm that efficiently trades off complexity and approximation performance for overcomplete signal expansions. Finding the sparsest representation of a signal using a redundant dictionary is, in general, a NP-Hard problem. Even sub-optimal algorithms such as Matching Pursuit remain highly complex. We propose a structuring strategy that can be applied to any redundant set of functions, and which basically groups similar atoms together. A measure of similarity base

Distributed stream processing represents a novel computing paradigm where data, sensed externally and possibly preprocessed, is pushed asynchronously to various connected computing devices with heterogeneous capabilities for processing. It enables novel applications typically characterized by the need to process high-volume data streams in a timely and responsive fashion. Some example applications include sensor networks, location-tracking services, distributed speech recognition, and network management. Re

The distributed representation of correlated multi-view images is an important problem that arise in vision sensor networks. This paper concentrates on the joint reconstruction problem where the distributively compressed correlated images are jointly decod ...

The paper addresses the media-specific rate allocation problem in multipath networks. The streaming rate on each path is determined such that the end- to-end media distortion is minimized, when the receiving client aggregates packets received via multiple ...

Multiview video has recently emerged as a means to improve user experience in novel multimedia services. We propose a new stochastic model to characterize the traffic generated by a Multiview Video Coding (MVC) variable bit-rate source. To this aim, we res ...

This paper proposes a new method for the selection of sets of omnidirectional views, which contribute together to the efficient representation of a 3d scene. When the 3d surface is modelled as a function on a unit sphere, the view selection problem is mostly governed by the accuracy of the 3d surface reconstruction from non-uniformly sampled datasets. A novel method is proposed for the reconstruction of signals on the sphere from scattered data, using a generalization of the Spherical Fourier Transform. Wit

We address the problem of delay-constrained streaming of multimedia packets over dynamic bandwidth channels. Efficient streaming solutions generally rely on the knowledge of the channel bandwidth, in order to select the media packets to be transmitted, according with their sending time. However, the streaming server usually cannot have a perfect knowledge of the channel bandwidth, and important packets may be lost because of over-estimation. We address the rate prediction mismatch by media scheduling with a

In this paper, we address the problemof super-resolution from multiple low-resolution omnidirectional images with inexact registration. Such a problem is typically encountered in omnidirectional vision scenarios with reduced resolution sensors in imperfect ...

Growth codes are a subclass of Rateless codes that have found interesting applications in data dissemination problems. Compared to other Rateless and conventional channel codes, Growth codes show improved intermediate performance which is particularly usef ...

We address the problem of video quality prediction and control for high-resolution video transmitted over lossy packet networks. In packet video, the bitstream flows through several subsystems (coder, network, decoder); each of them can impair the information, either by data loss or by introducing some delay. However, each of these subsystems can be fine- tuned in order to minimize these problems and to optimize the quality of the delivered signal, taking into account the available bitrate. The assessment o

Accurate segmentation of coronary arteries remains a significant challenge in clinical practice, hindering the ability to effectively diagnose and manage coronary artery disease. The lack of large, annotated datasets for model training exacerbates this issue, limiting the development of automated tools that could assist radiologists. To address this, we introduce CM-UNet, which leverages self-supervised pre-training on unannotated datasets and transfer learning on limited annotated data, enabling accurate d

This paper addresses the problem of dense disparity estimation in networks of omnidirectional cameras. We propose to map omnidirectional images on the 2-sphere, and we perform disparity estimation directly on the sphere in order to preserve the geometry of images. We ﬁrst perform rectiﬁcation of the images in the spherical domain. Then we formulate a global energy minimization problem for the estimation of disparity on the sphere. We solve the optimization problem with a graph-cut algorithm, and we show tha

Deep Neural Networks have achieved extraordinary results on image classification tasks, but have been shown to be vulnerable to attacks with carefully crafted perturbations of the input data. Although most attacks usually change values of many image's pixe ...

The construction of a meaningful graph plays a crucial role in the success of many graph-based representations and algorithms for handling structured data, especially in the emerging field of graph signal processing. However, a meaningful graph is not alwa ...

We consider the problem of energy-efficient on-line scheduling for slice-parallel video decoders on multicore systems. We assume that each of the processors are Dynamic Voltage Frequency Scaling (DVFS) enabled such that they can independently trade off per ...

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 the consensus algorithm in order to design an efficient progressive quantization scheme. We implement a fixed-resolution uniform quantizer in each sensor, where refined quantization is achieved by reducing the quantization intervals with the convergence of

Pascal Frossard

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Wyner-Ziv coding of multi-view omnidirectional images with overcomplete decompositions

Media coding for streaming in networks with source and path diversity

AI-Driven multi-view learning from CCTA for myocardial infarction diagnosis

Optimal Representations for Adaptive Streaming in Interactive Multiview Video Systems

Tree-Based Pursuit: Algorithm and Properties

Signal Processing Challenges in Distributed Stream Processing Systems

Joint Reconstruction of Multi-view Compressed Images

Distributed Media Rate Allocation in Multipath Networks

A Poisson Hidden Markov Model for Multiview Video Traffic

Omnidirectional views selection for scene representation

Media Streaming with Conservative Delay on Variable Rate Channels

l1 Regularized Super-resolution From Unregistered Omnidirectional Images

Growth Codes: Intermediate Performance Analysis and Application to Video

User-Oriented QoS Analysis in MPEG-2 Video Delivery

CM-UNet: A Self-Supervised Learning-Based Model for Coronary Artery Segmentation in X-Ray Angiography

Dense Depth Estimation from Omnidirectional Images

SparseFool: a few pixels make a big difference

Learning Laplacian Matrix in Smooth Graph Signal Representations

Markov Decision Process Based Energy-Efficient On-Line Scheduling for Slice Parallel Video Decoders on Multicore Systems

Progressive quantization in distributed average consensus