Digital watermarking is a key ingredient to copyright protection. It provides a solution to illegal copying of digital material and has many other useful applications such as broadcast monitoring and the recording of electronic transactions. Now, for the first time, there is a book that focuses exclusively on this exciting technology. Digital Watermarking covers the crucial research findings in the field: it explains the principles underlying digital watermarking technologies, describes the requirements that have given rise to them, and discusses the diverse ends to which these technologies are being applied. As a result, additional groundwork is laid for future developments in this field, helping the reader understand and anticipate new approaches and applications.

Digital Watermarking

User Generated Content (UGC) is re-shaping the way people watch video and TV, with millions of video producers and consumers. In particular, UGC sites are creating new viewing patterns and social interactions, empowering users to be more creative, and developing new business opportunities. To better understand the impact of UGC systems, we have analyzed YouTube, the world's largest UGC VoD system. Based on a large amount of data collected, we provide an in-depth study of YouTube and other similar UGC systems. In particular, we study the popularity life-cycle of videos, the intrinsic statistical properties of requests and their relationship with video age, and the level of content aliasing or of illegal content in the system. We also provide insights on the potential for more efficient UGC VoD systems (e.g. utilizing P2P techniques or making better use of caching). Finally, we discuss the opportunities to leverage the latent demand for niche videos that are not reached today due to information filtering effects or other system scarcity distortions. Overall, we believe that the results presented in this paper are crucial in understanding UGC systems and can provide valuable information to ISPs, site administrators, and content owners with major commercial and technical implications.

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I tube, you tube, everybody tubes: analyzing the world's largest user generated content video system

An interactive television program guide with remote access is provided. The interactive television program guide is implemented on interactive television program guide equipment. A remote program guide access device is connected to the interactive television program guide equipment by a remote access link to provide a user with remote access to program guide functions. An interactive television program guide system based on multiple user television equipment devices in a single household is provided. The system provides a user with an opportunity to adjust program guide settings with a given one of the interactive television program guides. Program guide setting include features related to setting program reminders, profiles, program recording features, messaging features, favorites features, parental control features, program guide set up features (e.g., audio and video and language settings), etc.

Interactive television program guide with remote access

A system for integrating video programming with the vast information resources of the Internet. A computer-based system receives a video program with embedded uniform resource locators (URLs). The URLs, the effective addresses of locations or Web sites on the Internet, are interpreted by the system and direct the system to the Web site locations to retrieve related Web pages. Upon receipt of the Web pages by the system, the Web pages are synchronized to the video content for display. The video program signal can be displayed on a video window on a conventional personal computer screen. The actual retrieved Web pages are time stamped to also be displayed, on another portion of the display screen, when predetermined related video content is displayed in the video window. As an alternative, the computer-based system receives the URLs directly through an Internet connection, at times specified by TV broadcasters in advance. The system interprets the URLs and retrieves the appropriate Web pages. The Web pages are synchronized to the video content for display in conjunction with a television program being broadcast to the user at that time. This alternative system allows the URLs to be entered for live transmission to the user.

Enhanced video programming system and method for incorporating and displaying retrieved integrated Internet information segments

A system and method for scheduling the receipt of desired movies and other forms of data from a network which simultaneously distributes many sources of such data to many customers, as in a cable television system. Customer profiles are developed for the recipient describing how important certain characteristics of the broadcast video program, movie or other data are to each customer. From these profiles, an 'agreement matrix' (908) is calculated by comparing the recipient's profiles to the actual profiles of the characteristics of the available video programs, movies, or other data. The agreement matrix (908) thus characterizes the attractiveness of each video program, movie, or other data to each prospective customer. 'Virtual' channels are generated from the agreement matrix (908) to produce a series of video or data programming which will provide the greatest satisfaction to each customer. Feedback paths (1020, 1024) are also provided so that the customer's profiles and/or the profiles of the video programs or other data may be modified to reflect actual usage, and so that the data downloaded to the customer's set top terminal (620) may be minimized. Kiosks (figure 11) are also developed which assist customers in the selection of videos, music, books, and the like in accordance with the customer's objective profiles.

System and method for scheduling broadcast of and access to video programs and other data using customer profiles

Even though shared-memory concurrency is a paradigm frequently used for developing parallel applications on small- and middle-sized machines, experience has shown that it is hard to use. This is largely caused by synchronization primitives which are low-level, inherently non-deterministic, and, consequently, non-intuitive to use. In this paper, we present the Nornir run-time system. Nornir is comparable to well-known frameworks such as MapReduce and Dryad that are recognized for their efficiency and simplicity. Unlike these frameworks, Nornir also supports process structures containing branches and cycles. Nornir is based on the formalism of Kahn process networks, which is a shared-nothing, message-passing model of concurrency. We deem this model a simple and deterministic alternative to shared-memory concurrency. Experiments with real and synthetic benchmarks on up to 8 CPUs show that performance in most cases scales almost linearly with the number of CPUs, when not limited by data dependencies. We also show that the modeling flexibility allows Nornir to outperform its MapReduce counterparts using well-known benchmarks.

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The Nornir run-time system for parallel programs using Kahn process networks on multi-core machines—a flexible alternative to MapReduce

One of the most common ways of capturing wide eld-of-view scenes is by recording panoramic videos. Using an array of cameras with limited overlapping in the corresponding images, one can generate good panorama images. Using the panorama, several immersive display options can be explored. There is a two fold synchronization problem associated to such a system. One is the temporal synchronization, but this challenge can easily be handled by using a common triggering solution to control the shutters of the cameras. The other synchronization challenge is the automatic exposure synchronization which does not have a straight forward solution, especially in a wide area scenario where the light conditions are uncontrolled like in the case of an open, outdoor football stadium. In this paper, we present the challenges and approaches for creating a completely automatic real-time panoramic capture system with a particular focus on the camera settings. One of the main challenges in building such a system is that there is not one common area of the pitch that is visible to all the cameras that can be used for metering the light in order to nd appropriate camera parameters. One approach we tested is to use the green color of the eld grass. Such an approach provided us with acceptable results only in limited light conditions.A second approach was devised where the overlapping areas between adjacent cameras are exploited, thus creating pairs of perfectly matched video streams. However, there still existed some disparity between di erent pairs. We nally developed an approach where the time between two temporal frames is exploited to communicate the exposures among the cameras where we achieve a perfectly synchronized array. An analysis of the system and some experimental results are presented in this paper. In summary, a pilot-camera approach running in auto-exposure mode and then distributing the used exposure values to the other cameras seems to give best visual results.

Automatic exposure for panoramic systems in uncontrolled lighting conditions: a football stadium case study

Energy consumption is an important concern for mobile devices, where the evolution in battery storage capacity has not followed the power usage requirements of modern hardware. However, innovative and flexible hardware platforms give developers better means of optimising the energy consumption of their software. For example, the Tegra K1 System-on-Chip (SoC) offers two CPU clusters, GPU offloading, frequency scaling and other mechanisms to control the power and performance of applications. In this demonstration, the scenario is live video encoding, and participants can experiment with power usage and performance using the Tegra K1's hardware capabilities. A popular power-saving approach is a "race to sleep" strategy where the highest CPU frequency is used while the CPU has work to do, and then the CPU is put to sleep. Our own experiments indicate that an energy reduction of 28 % can be achieved by running the video encoder on the lowest CPU frequency at which the platform achieves an encoding frame rate equal to the minimum frame rate of 25 Frames Per Second (FPS).

Energy efficient video encoding using the tegra K1 mobile processor

Video streaming is one of the top traffic contributors in the Internet and a frequent research subject. It is expected that streaming traffic will grow 4-fold for video globally and 9-fold for mobile video between 2017 and 2022. In this paper, we present an automatized measurement framework for evaluating video streaming QoE in operational broadband networks, using headless streaming with a Docker-based client, and a server-side implementation allowing for the use of multiple video players and adaptation algorithms. Our framework allows for integration with the acsMONROE testbed and Bitmovin Analytics, which bring on the possibility to conduct large-scale measurements in different networks, including mobility scenarios, and monitor different parameters in the application, transport, network, and physical layers in real-time.

https://dl.acm.org/doi/pdf/10.1145/3343031.3350538

Docker-Based Evaluation Framework for Video Streaming QoE in Broadband Networks

The Round-Trip Time (RTT) is a property of the path between a sender and a receiver communicating with Transmission Control Protocol (TCP) over an IP network and over the public Internet. The end-to-end RTT value influences significantly the dynamics and performance of TCP, which is by far the most used communication protocol. Thus, in communication networks, RTT is an important network performance variable. By measuring the traffic at an intermediate node, a network operator or service provider can estimate the RTT and use the estimation to study and troubleshoot the per-connection characteristics and performance. This paper aims at improving the accuracy and timeliness of the RTT estimation, to help network operators improving their analysis. We propose and evaluate a novel deep learning-based model capable of dynamically predicting at real-time the RTT between the sender and receiver with high accuracy based on passive measurements collected at an intermediate node, taking advantage of the commonly used TCP timestamps. We validate extensively our prediction methodology in a controlled experimental testbed and in a realistic scenario on the Google Cloud platform. We show that our model, which is based on classical deep learning algorithms, gives reasonably effective state-of-the-art performance results across multiple TCP congestion control variants. We also show that the model works well for transfer learning. Even though the RTT prediction model was trained on an emulated network, it performs well also when applied to a realistic scenario setting, as demonstrated in our experimental evaluation.

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Carsten Griwodz

Papers

The Nornir run-time system for parallel programs using Kahn process networks on multi-core machines—a flexible alternative to MapReduce

Automatic exposure for panoramic systems in uncontrolled lighting conditions: a football stadium case study

Energy efficient video encoding using the tegra K1 mobile processor

Docker-Based Evaluation Framework for Video Streaming QoE in Broadband Networks

A Deep Learning Approach to Dynamic Passive RTT Prediction Model for TCP