C. De Vleeschouwer

Circular interpretation of bijective transformations in lossless watermarking for media asset management

The need for reversible or lossless watermarking methods has been highlighted in the literature to associate subliminal management information with losslessly processed media and to enable their authentication. The paper first analyzes the specificity and the application scope of lossless watermarking methods. It explains why early attempts to achieve reversibility are not satisfactory. They are restricted to well-chosen images, strictly lossless context and/or suffer from annoying visual artifacts. Circular interpretation of bijective transformations is proposed to implement a method that fulfills all quality and functionality requirements of lossless watermarking. Results of several bench tests demonstrate the validity of the approach.

Watermarking algorithm based on a human visual model

This paper presents an additive watermarking technique for grey-scale pictures. It consists in secretly embedding copyright information (a binary code) into the picture without degrading its quality. Those bits are encoded through the phase of maximal length sequences (MLS). MLS are binary sequences with good correlation properties. The result of the autocorrelation is much greater than crosscorrelations, i.e; correlations made with shifted versions of this sequence. The embedded bits are retrieved from the result of the correlations. The core of the embedding process is underlaid by a masking criterion that guarantees the invisibility of the watermark. It is combined with an edge and texture discrimination to determine the embedding level of the MLS, whose bits are actually spread over 32 x 8 pixel blocks. Eventually, some results are presented, which analyze the efficiency of the retrieval as well as the resistance of the watermark to compression and its robustness against malevolent manipulation

Invisibility and application functionalities in perceptual watermarking an overview

Digital watermarking consists of hiding subliminal information into digital media content, also called host data. It can be the basis of many applications, including security and media asset management. In this paper we focus on the imperceptibility requirement for image watermarking. We first provide a functional inventory of image watermarking applications and emphasize the dependency between the application purpose and its need for invisibility. Then, we present a global framework common to most existing watermarking systems. It illustrates the methodology followed to translate human vision research into watermarking technology. It suggests future prospects and highlights the need for dedicated inputs from the human vision community.

Overview on Selective Encryption of Image and Video: Challenges and Perspectives

In traditional image and video content protection schemes, called fully layered, the whole content is first compressed. Then, the compressed bitstream is entirely encrypted using a standard cipher (DES, AES, IDEA, etc.). The specific characteristics of this kind of data (high-transmission rate with limited bandwidth) make standard encryption algorithms inadequate. Another limitation of fully layered systems consists of altering the whole bitstream syntax which may disable some codec functionalities. Selective encryption is a new trend in image and video content protection. It consists of encrypting only a subset of the data. The aim of selective encryption is to reduce the amount of data to encrypt while preserving a sufficient level of security. This computation saving is very desirable especially in constrained communications (real-time networking, high-definition delivery, and mobile communications with limited computational power devices). In addition, selective encryption allows preserving some codec functionalities such as scalability. This tutorial is intended to give an overview on selective encryption algorithms. The theoretical background of selective encryption, potential applications, challenges, and perspectives is presented.

Receiver-driven bandwidth sharing for TCP

Applications using TCP, such as Web-browsers, ftp, and various P2P programs, dominate most of the Internet traffic today. In many cases the last-hop access links are bottlenecks due to their limited bandwidth capability with users running many simultaneous network applications. Standard TCP shares bottleneck link capacity according to connection round-trip time (RTT), and may result in a bandwidth partition which does not necessarily coincide with the users desires. We present a receiver-based control system for allocating bandwidth among TCP flows according to user preferences. Our system does not require any changes to network infrastructure, and works with standard TCP senders. NS-2 simulations, as well as actual Internet experiments, show that our system achieves desired bandwidth allocation in a wide variety of scenarios including interfering cross-traffic. We also demonstrate the viability of our system in multimedia streaming applications over TCP.

Receiver-driven bandwidth sharing for TCP and its application to video streaming

Applications using Transmission Control Protocol (TCP), such as web-browsers, ftp, and various peer-to-peer (P2P) programs, dominate most of the Internet traffic today. In many cases, users have bandwidth-limited last mile connections to the Internet which act as network bottlenecks. Users generally run multiple concurrent networking applications that compete for the scarce bandwidth resource. Standard TCP shares bottleneck link capacity according to connection round-trip time (RTT), and consequently may result in a bandwidth partition which does not necessarily coincide with the users desires. In this work, we present a receiver-based bandwidth sharing system (BWSS) for allocating the capacity of last-hop access links according to user preferences. Our system does not require modifications to the TCP protocol, network infrastructure or sending hosts, making it easy to deploy. By breaking fairness between flows on the access link, the BWSS can limit the throughput fluctuations of high-priority applications. We utilize the BWSS to perform efficient video streaming over TCP to receivers with bandwidth-limited last mile connections. We demonstrate the effectiveness of our proposed system through Internet experiments.

An Autonomous Framework to Produce and Distribute Personalized Team-Sport Video Summaries: A Basketball Case Study

Democratic and personalized production of multimedia content is a challenge that content providers will have to face in the near future. In this paper, we address this challenge by building on computer vision tools to automate the collection and distribution of audiovisual content. Especially, we proposed a complete production process of personalized video summaries in a typical application scenario, where the sensor network for media acquisition is composed of multiple cameras, which, for example, cover a basketball field. Distributed analysis and interpretation of the scene are exploited to decide what to show or not to show about the event, so as to produce a video composed of a valuable subset of the streams provided by each individual camera. Interestingly, the selection of the streams subsets to forward to each user depends on his/her individual preferences, making the process adaptive and personalized. The process involves numerous integrated technologies and methodologies, including but not limited to automatic scene analysis, camera viewpoint selection, adaptive streaming, and generation of summaries through automatic organization of stories. The proposed technology provides practical solutions to a wide range of applications, such as personalized access to local sport events through a web portal, cost-effective and fully automated production of content dedicated to small-audience, or even automatic log in of annotations.

Automatic detection of interest areas of an image or of a sequence of images

The tool introduced in this paper allows to automatically decide in an image or in a video sequence which regions are important and which ones are not. For this purpose, fuzzy logic has been used to modelize human subjective knowledge about the way to allocate priorities to regions. The resulting classification can be used in a wide range of applications going from image coding to image understanding.

Prefetching and Caching Strategies for Remote and Interactive Browsing of JPEG2000 Images

This paper considers the issues of scheduling and caching JPEG2000 data in client/server interactive browsing applications, under memory and channel bandwidth constraints. It analyzes how the conveyed data have to be selected at the server and managed within the client cache so as to maximize the reactivity of the browsing application. Formally, to render the dynamic nature of the browsing session, we assume the existence of a reaction model that defines when the user launches a novel command as a function of the image quality displayed at the client. As a main outcome, our work demonstrates that, due to the latency inherent to client/server exchanges, a priori expectation about future navigation commands may help to improve the overall reactivity of the system. In our study, the browsing session is defined by the evolution of a rectangular window of interest (WoI) along the time. At any given time, the WoI defines the position and the resolution of the image data to display at the client. The expectation about future navigation commands is then formalized based on a stochastic navigation model, which defines the probability that a given WoI is requested next, knowing previous WoI requests. Based on that knowledge, several scheduling scenarios are considered. The first scenario is conventional and transmits all the data corresponding to the current WoI before prefetching the most promising data outside the current WoI. Alternative scenarios are then proposed to anticipate prefetching, by scheduling data expected to be requested in the future before all the current WoI data have been sent out. Our results demonstrate that, for predictable navigation commands, anticipated prefetching improves the overall reactivity of the system by up to 30% compared to the conventional scheduling approach. They also reveal that an accurate knowledge of the reaction model is not required to get these significant improvements

Robust image hashing based on radial variance of pixels

Robust image hashing defines a feature vector that characterizes the image, independently of non-significant distortions of its content. As a consequence, the comparison between robust image hash vectors is able to indicate whether the corresponding images are equivalent or not, independently of visually non-significant distortions due for example to compression or re-sampling. We define a robust image hash based on radial projections of the image pixels. Specifically, our proposed radial hASH (RASH) considers moments of different orders to describe the luminance pdf of the pixels encountered on a set of lines articulated around the center of the image. In short, each RASH component is defined based on the moment of the pixels belonging to a specific line. Our paper provides a careful analysis of the robustness and discriminating capabilities of the RASH vectors computed based on different moment orders. As a first contribution, it demonstrates that the second order moment, i.e. the variance of the pixels on a line, allows for optimal trade-offs between the robustness and the discriminating capabilities of the resulting RASH vector. As a second contribution, extensive simulations prove that a decision engine based on RASH vectors cross-correlations is able to successfully identify pairs of equivalent or distinct images. Bottom line, the RASH assets are a low computational complexity, a strong robustness to both filtering and geometrical distortions, and a risk of collision that is estimated to less than 10 per million of images.