Streaming Media

The objective of this study is to develop the transmitting environment simulation of uncompressed highdefinition (HD) video system over Additive White Gaussian Noise (AWGN) channel. This system analyzes and compares the Peak Signal-to-Noise Ratio (PSNR) performance over 16-QAM and QPSK modulation. Equal Error Protection (EEP) and Unequal Error Protection (UEP) methods for video streaming are also incorporated. In this paper, a selection modulation method is proposed to achieve a high quality picture for video streaming. By using this approach, an optimal solution of PSNR values can be maintained over different kinds of channel conditions.

Learning Management Systems (LMSs) are applications that facilitate the management, observation and delivery of educational material through the Internet. Nowadays several of these systems are of such high quality that despite their free distribution and open source nature they are gaining popularity among distinct academic institutions. This paper addresses the issue of installing and adopting the open source LMS Dokeos to deliver SCORM lessons in the Greek language. Additionally, the authors demonstrate the extension of the system with direct support for new services such as videoconferencing and streaming video. The proposed methodology is applicable to any LMSs and therefore can function as the basis for coping with similar localization problems in discrete e-learning platforms.

This paper addresses the challenge of assessing and modeling Quality of Experience (QoE) for online video services that are based on TCP-streaming. We present a dedicated QoE model for YouTube that takes into account the key influence factors (such as stalling events caused by network bottlenecks) that shape quality perception of this service. As second contribution, we propose a generic subjective QoE assessment methodology for multimedia applications (like online video) that is based on crowdsourcing -a highly cost-efficient, fast and flexible way of conducting user experiments. We demonstrate how our approach successfully leverages the inherent strengths of crowdsourcing while addressing critical aspects such as the reliability of the experimental data obtained. Our results suggest that, crowdsourcing is a highly effective QoE assessment method not only for online video, but also for a wide range of other current and future Internet applications.

This paper presents an estimation of Quality of Experience (QoE) metrics based on Quality of Service (QoS) metrics in WiMAX networks. Applications used to generate such estimations were EvalVid and Network Simulator 2 (NS-2). The QoE was estimated by employing a Multilayer Artificial Neural Network by means of the WEKA tool. The results show a very efficient estimation of metrics of QoE parameters with respect to QoS parameters.

In this paper, we discuss the problem of distributing streaming media content, both live and on-demand, to a large number of hosts in a scalable way. Our work is set in the context of the traditional client-server framework. Specifically, we consider the problem that arises when the server is overwhelmed by the volume of requests from its clients. As a solution, we propose Cooperative Networking (CoopNet), where clients cooperate to distribute content, thereby alleviating the load on the server. We discuss the proposed solution in some detail, pointing out the interesting research issues that arise, and present a preliminary evaluation using traces gathered at a busy news site during the flash crowd that occurred on September 11, 2001.

To improve the robustness of video transmission over heterogeneous wireless network various error resilient tools are deployed. The impact of bit errors on the perceived video quality depends on several factors, such as error resilience of the data format, error concealment mechanism used and characteristics of the bit error pattern. In this paper the impact of bit error is analyzed and various error resilient tools implemented at the transmitter side, at the receiver and the ones requiring interactive feedback on dynamic channel conditions are discussed. The paper also covers a few cross layer optimization techniques.

Manipulation of XML data is becoming increasingly important for multimedia retrieval. Several encouraging attempts at developing methods for searching data have been proposed. However, efficiency and simplicity are still a barrier for further development. This paper gives a global idea about our multimodal system for retrieval multimedia annotated documents. This system combines four retrieval modalities: first by keywords, second by visual graph, third Query by Resources and finally using standardized languages.

Accurate temperature measurement in industrial environments is as important as it is challenging. Precise control over temperature measurement is crucial when processing metals, such as iron or steel, where temperature monitoring is critical to productivity and product quality. In the steel manufacturing process, temperature measurement of molten pig iron is particularly important, as it is a required parameter of the

The advent of infrastructureless vehicle-to-vehicle 4 (V2V) communication has opened the opportunity to design 5 driver-assistance systems that collect information from sensors 6 residing in neighboring vehicles. Windshield-installed cameras are 7 one example of a sensor that is becoming common in modern vehi-8 cles. Remotely accessing real-time images of these cameras using 9 V2V communication enables a significant increase in the visual 10 awareness of each driver. In this paper, we propose and evaluate 11 the performance of a driver-assistance system that leverages on 12 V2V communication and windshield-installed cameras to trans-13 form vision-obstructing vehicles into transparent tubular objects. 14 This cooperative system is able to increase the visibility of drivers 15 intending to overtake, thus making such critical maneuvers safer. 16 Our system uses an augmented reality human-machine interface 17 that is able to convey the increased visibility perspective in a 18 straightforward fashion. We also show that the required latency 19 for this intervehicle communication can be obtained using the 20 Dedicated Short-Range Communications (DSRC) proposed for 21 vehicular environments.

Digital streaming media services are increasingly common in ever more segments of the media industries. Frequent calls for a Spotify or a Netflix for books, magazines or newspapers illustrate how such services are seen to answer to the demands of audiences and producers alike. Moreover, such appeals reveal how streaming is seen as a universal model for all kinds of digitized media that have previously been distributed through various other channels. Digitalization of the media industries has seen a number of more or less ground-breaking and disruptive innovations of a technological kind; meanwhile, many have found it hard to establish financially viable digital solutions. As such, streaming media represent the hope of finding a sustainable business model in the digital era. Based in readings of existing literature, industry reports, and press reports, this paper examines streaming media services across various media industries including book, magazine and comics publishing, television, computer games, film, music and newspapers. It employs a theoretical framework of innovation theory as applied to the media industries coupled with concepts derived from media management and new media studies. The main objective is to map the field of streaming media across media industries and to start to categorize various models for simultaneous online provision of media under more precise terms, the most evident being to explicate and elaborate what can be meant by “A Spotify for X” or “A Netflix for X”.

The Internet is today a world wide packet switching arena constituting enormous possibilities of new services and business creation. E.g., there is a clear tendency that more and more real-time services are making the jump from dedicated circuit-switched and broadcasting networks into packet switching. Examples are telephony, videoconferencing, and television. The Internet today is thus hosting a large set of different services, including the delay tolerant Web-surfing traffic, but also the non-delay tolerant real-time services. An additional challenge with most real-time traffic is that its traffic pattern do not adapt to the varying traffic load as Web-traffic do. Still, these new services work well, as long as the packet switching capacity is sufficient. Problems arise when the growth of real-time service usage is larger than the capacity increase. During peak hours, users will then start to experience media services fall-out and excessive communication delay.

We provide an overview of an architecture of today's Internet streaming media delivery networks and describe various problems that such systems pose with regard to video coding. We demonstrate that based on the distribution model (live or on-demand), the type of the network delivery mechanism (unicast versus multicast), and optimization criteria associated with particular segments of the network (e.g., minimization of distortion for a given connection rate, minimization of traffic in the dedicated delivery network, etc.), it is possible to identify several models of communication that may require different treatment from both source and channel coding perspectives. We explain how some of these problems can be addressed using a conventional framework of temporal motion-compensated, transform-based video compression algorithm, supported by appropriate channel-adaptation mechanisms in client and server components of a streaming media system. Most of these techniques have already been implemented in RealNetworks(R) RealSystem(R) 8 and its RealVideo(R) 8 codec, which we use throughout the paper to illustrate our results

This paper makes an investigation of the dehazing effects on image and video coding for surveillance systems. The goal is to achieve good dehazed images and videos at the receiver while sustaining low bitrates (using compression) in the transmission pipeline. At first, this paper proposes a novel method for single-image dehazing, which is used for the investigation. It operates at a faster speed than current methods and can avoid halo effects by using the median operation. We then consider the dehazing effects in compression by investigating the coding artifacts and motion estimation in cases of applying any dehazing method before or after compression. We conclude that better dehazing performance with fewer artifacts and better coding efficiency is achieved when the dehazing is applied before compression. Simulations for Joint Photographers Expert Group images in addition to subjective and objective tests with H.264 compressed sequences validate our conclusion.

With SOAP-based Web Services leaving the stadium of being an explorative set of new technologies and entering the stage of mature and fundamental building blocks for service-driven business processes-and in some cases even for mission critical systems-, the demand for non-functional requirements including efficiency as well as security and dependability commonly increase rapidly. Although, Web Services are capable of coupling heterogeneous information systems in a flexible and cost-efficient way, the processing efficiency and robustness against certain attacks do not fulfill industry-strength requirements. In this paper, a comprehensive stream-based WS-Security processing system is introduced, which enables a more efficient processing in service computing and increases the robustness against different types of Denial-of-Service (DoS) attacks. The introduced engine is capable of processing all standard-conforming applications of WS-Security in a streaming manner. It can handle e.g. any order, number and nesting degree of signature and encryption operations, closing the gap towards more efficient and dependable Web Services.

Mobile world's rapid growth has spurred development of new protocols and new algorithms to meet changing operation requirements such as mobile networking, and quality-of-service support. A key requirement in the bearer capabilities is the handover. The freedom to be able to make and receive calls anywhere, at any time, creating a totally new dimension in human communications has frequently been advertised as the main advantage of new wireless systems. Handovers are a key concept in providing this mobility. It makes it possible for a user to travel from one cell to another while having a seamless connection. Network operators give emphasis to optimize handover, since it is strongly related to dropped calls, network overload and subsequently users' criticism. The ability of a cellular network to perform efficient handovers is crucial to offer attractive services as real-time applications or streaming media as planned in third generation networks. Since signal propagation and pathloss are complex in nature, we can expect unnecessary and wrong handoff executions. Both UMTS and those of the second generation (GSM) systems will require redefined handoff algorithms of active connections as the smooth mobility support and continuous connection are essential issues for obtaining high performance and increasing user satisfaction. In this paper we present a set of intelligent algorithms using the mobile terminal (MT) location information and area awareness to assist safe handoff decisions. The implemented algorithms are validated by means of cellular network simulators that clearly show the impact of these techniques to major system performance metrics.

Delay-sensitive video transmission over IEEE 802.11 wireless local area networks (WLANs) is analyzed in a cross-layer optimization framework. The effect of delay constraint on the quality of received packets is studied by analyzing “expired-time packet discard rate”. Three analytical models are examined and it is shown that M/M/1 model is quite an adequate model for analyzing delay-limited applications such as

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Traffic sign recognition (TSR) is one of the most important background research topics for enabling autonomous vehicle driving systems. Autonomous driving systems require special handling of input data: there is no time for complex transformations or sophisticated image processing techniques, they need a solid and real-time analysis of a situation. This challenge get more difficult to meetin a city like environment where multiple traffic signs, ads, parking vehicles, pedestrians, and other moving or background objects make the recognition much more difficult. While numerous solutions have been published, solutions are tested on autoways, country-side, or at a very low speed. In this paper, we give a short overview on main problems and known strategies to solve these problems, and we give a general solution to tackle real-time issues in urban traffic sign recognition.

Urban traffic control systems have based their technological infrastructure both on advanced analogical close-circuit television systems (TVCC) and point-topoint links, providing low-scalable and very expensive systems. The main goal of an urban traffic monitoring system is to capture, send, play and distribute video information from the streets of a certain city. Current digitalization process of video networks, and the research carried out in the field of streaming media, has led vendors to present proprietary hardware and software solutions resulting in a strong dependency among their customers. The existence of open standards for video encoding and protocols for streaming media transmission over IP networks has led us to propose this system. The work presents an open urban traffic control system which bases its design on COTS philosophy for hardware and software, as well as open source and standardized protocols. The proposed system is a suitable solution in terms of scalability, cost, interoperability and performance for traffic control systems. Futhermore, its architecture can be easily adapted to other video applications and tools.

Due to the explosive growth of the Internet and increasing demand for multimedia information on the web, streaming video over the Internet has received tremendous attention from academia and industry. Transmission of real-time video typically has bandwidth, delay, and loss requirements. However, the current best-effort Internet does not offer any quality of service (QoS) guarantees to streaming video. Furthermore, for video multicast, it is difficult to achieve both efficiency and flexibility. Thus, Internet streaming video poses many challenges. To address these challenges, extensive research has been conducted. This special issue is aimed at dissemination of the contributions in the field of streaming video over the Internet. To introduce this special issue with the necessary background and provide an integral view on this field, we cover six key areas of streaming video. Specifically, we cover video compression, application-layer QoS control, continuous media distribution services, streaming servers, media synchronization mechanisms, and protocols for streaming media. For each area, we address the particular issues and review major approaches and mechanisms. We also discuss the tradeoffs of the approaches and point out future research directions.

In this work a novel approach to video temporal decomposition into semantic units, termed scenes, is presented. In contrast to previous temporal segmentation approaches that employ mostly low-level visual or audiovisual features, we introduce a technique that jointly exploits low-level and high-level features automatically extracted from the visual and the auditory channel. This technique is built upon the well-known method of the Scene Transition Graph (STG), first by introducing a new STG approximation that features reduced computational cost, and then by extending the unimodal STG-based temporal segmentation technique to a method for multimodal scene segmentation. The latter exploits, among others, the results of a large number of TRECVID-type trained visual concept detectors and audio event detectors, and is based on a probabilistic merging process that combines multiple individual STGs while at the same time diminishing the need for selecting and fine-tuning several STG construction parameters. The proposed approach is evaluated on three test datasets, comprising TRECVID documentary films, movies, and news-related videos, respectively. The experimental results demonstrate the improved performance of the proposed approach in comparison to other unimodal and multimodal techniques of the relevant literature and highlight the contribution of high-level audiovisual features towards improved video segmentation to scenes. P.

This paper proposes a novel quality-oriented algorithm for multiple-source delivery of multimedia over heterogeneous wireless networks, which enables maintaining high levels of user-perceived quality. Unlike existing solutions, which perform delivery adaptation by adjusting the original multimedia quality to varying network conditions, this solution is based on dynamically balancing the multimedia content among multiple streams in order to achieve its goal. The proposed scheme and three other known approaches are compared in terms of estimated user-perceived quality. Simulation results show how this scheme outperforms the other solutions, including cases where the number of simultaneous receivers increases significantly. In addition, real environment tests show how the proposed scheme provides higher quality in terms of both objective and subjective metrics than competing approaches.

This paper introduces and analyzes a class of nonlinear congestion control algorithms called binomial algorithms, motivated in part by the needs of streaming audio and video applications for which a drastic reduction in transmission rate upon each congestion indication (or loss) is problematic. Binomial algorithms generalize TCP-style additive-increase by increasing inversely proportional to a power ¢ of the current window (for TCP, ¢ ¤ £ ¦ ¥ ) ; they generalize TCP-style multiplicative-decrease by decreasing proportional to a power § of the current window (for TCP, § £ ©

Distributed media streaming, which uses multiple senders to collaboratively and simultaneously stream media content to a receiver, poses new challenges in congestion control. Such approach establishes multiple flows within a session. Since conventional congestion control only aims to make each of these flows TCP-friendly, selfish users can increase the number of flows to grab a larger share of the bandwidth, introducing more congestion and degrading the overall network performance. To address this issue, we propose the idea of task-level TCPfriendliness, which enforces TCP-friendliness upon a set of flows belonging to a task instead of upon individual flow. We design DMSCC, a congestion control scheme, to achieve task-level TCP-friendliness in distributed media streaming. By observing shared congestion, DMSCC identifies the set of flows experiencing congestion and dynamically adjusts those flows such that their combined throughput is TCP-friendly. To achieve this goal, DMSCC addresses two issues: (i) given a β (β < 1), how to control a flow using AIMD such that it consumes β-times the throughput of a TCP flow, and (ii) how to identify the set of flows that share a bottleneck. In our simulations, DMSCC can effectively regulate the throughput of flows on every bottleneck, resulting in a TCP-friendly combined throughput.

Segmented or data-partitioned H.264/AVC codec video streaming separates-out important information from the compressed bitstream and places it into separate packets. Because of the damaging impact of error bursts on real-time video streams, it has become common to apply application-layer forward error correction (FEC) for transport over broadband wireless access networks, herein IEEE 802.16e. In this paper an adaptive FEC scheme using Raptor coding is applied to segmented video. The paper sets out to answer the question whether equal or unequal error protection is preferable in that situation. Though UEP offers a reduction in bitrate there are multiple dB gains in video quality, which will prove attractive to end-users, if equal error protection is provided. Overhead from using EEP rather than UEP was found to be about 1% of the overall bitrate.

A novel analytic framework is devised for the performance modeling and eval- uation of a wireless 4G cell with bursty multiple class tra-c ∞ows consisting of voice calls, streaming media and data packets subject to an e-cient medium access control (MAC) protocol with a bufier threshold-based tra-c handling generalized partial sharing scheme (GPSS). In this context, an open queueing network

which enables the provisioning of multimedia services with Quality of Service (QoS) and mobility support across heterogeneous networks. The aim of this paper is twofold. First, to present a new fuzzy logic based Sender Bitrate (SBR) adaptation scheme at pre-encoding stage that is Quality of

This paper introduces and analyzes a class of nonlinear congestion control algorithms called binomial algorithms, motivated in part by the needs of streaming audio and video applications for which a drastic reduction in transmission rate upon each congestion indication (or loss) is problematic. Binomial algorithms generalize TCP-style additive-increase by increasing inversely proportional to a power ¢ of the current window (for TCP, ¢ ¤ £ ¦ ¥ ) ; they generalize TCP-style multiplicative-decrease by decreasing proportional to a power § of the current window (for TCP, § £ ©

S cen ar ios ar e n arr atives that illu s trate f u tu re p o ss ib ilities, s uch as p r o po s ed s y s tem s or p lan s , an d h elp p olicy m ak er s and d esig n ers ch oo s e am o n g alter n ativ e cou r s es o f action. In v iew o f th e d ecisio n-mak in g u s es to w h ich s cenar io s ar e p u t, it wo u ld b e v alu ab le to elab o r ate s cen ar io s at m u ltip le lev els o f d etail or to s u b s titu te d etailed ev entu alities b y s tar tin g f ro m a co m m on co re o f n ar r ativ e ep iso d es an d ref in in g th em dif f eren tly. A lth o u gh d o main-sp ecific tech n iq u es an d co m p u tatio nal en v ir on m en ts ex is t f or en co d ing s imu latin g and m anip u latin g s cenar io s, th er e ex is t n o g en er al-p u r po s e s cen ar io rep r esen tatio n s b etween th e ex tr em es o f fo r m ality an d in f o r mality p r ov id ed b y ex ecu tab le s im ulation p r og r am s at on e ex tr eme an d f r ee-f o r m text o r s tream ing m edia des cr ip tio ns at th e oth er. Th e ch allen g e is to d ef in e a r epr es entation f or s cen ar ios th at s u pp o r ts a wid e ran g e o f d is cus s io n an d co m pr eh ens io n activities w h ile r em ain in g ind ep en d en t o f co n tent an d acces s mech anis m s. O u r ap p ro ach is to d efin e a r ep res entation b ased o n th e m o r ph o lo gy o f n ar r ativ es an d th e activities o f sto r ytellin g , an ap pr o ach th at s epar ates w h at a nar r ativ e is f ro m h ow s cen ar ios ar e u s ed to s u p p or t d ecis ion m ak in g. Th is p ap er d escr ibes the r epr es entation , a m ar ku p im plem entation (SCML) , an d th eir u s e in th e m an ag emen t of s imu latio n ex p er im en ts. K E YW O R D S: S cen ar ios , h yp er med ia, s o f tw ar e en g ineer in g , In ter activ e n ar rative, X ML, collab or ation

Given rapid improvements in storage devices, network infrastructure and streaming-media technologies, a large number of corporations and universities are recording lectures and making them available online for anytime, anywhere access. However, producing high-quality lecture videos is still labor intensive and expensive. Fortunately, recent technology advances are making it feasible to build automated camera management systems to capture lectures. In this paper we report our design of such a system, including system configuration, audio-visual tracking techniques, software architecture, and user study. Motivated by different roles in a professional video production team, we have developed a multi-cinematographer single-director camera management system. The system performs lecturer tracking, audience tracking, and video editing all fully automatically, and offers quality close to that of human-operated systems.

This paper compares the performance of two algorithms for congestion control of streaming media. The two methods are Datagram Congestion Control Protocol (DCCP) over RED, and a solution based on an Active Queue Management (AQM) combined with explicit feedback of congestion level experienced at routers. DCCP relies on binary congestion met- rics, either as packet dropping or ECN marking at

Accurate temperature measurement in industrial environments is as important as it is challenging. Precise control over temperature measurement is crucial when processing metals, such as iron or steel, where temperature monitoring is critical to productivity and product quality. In the steel manufacturing process, temperature measurement of molten pig iron is particularly important, as it is a required parameter of the physical models used to control operations in steel furnaces. However, measuring the temperature of molten pig iron is not an easy task. Conventional methods using thermocouples or pyrometers present serious drawbacks which limit their applicability and do not provide accurate measurements. In this paper, an infrared computer vision system is proposed to measure the temperature of molten pig iron while it is being poured. The proposed system confronts two challenges: The stream must be detected in the infrared images, and the slag, which can partially cover the stream of molten pig iron, must be detected and removed from the stream. Fast, robust, and accurate methods are proposed. A calibration procedure for the emissivity of the molten pig iron and for the temperature level is also proposed and applied. This procedure makes it possible to differentiate molten pig iron from slag in the stream. Tests indicate that the results meet production needs.

In this paper we present two interactive systems for video search and browsing; one is a web application based on the Rich Internet Application paradigm, designed to obtain the levels of responsiveness and interactivity typical of a desktop application, while the other exploits multi-touch devices to implement a multi-user collaborative application. Both systems use the same ontology-based video search engine, that is capable of expanding user queries through ontology reasoning, and let users to search for specific video segments that contain a semantic concept or to browse the content of video collections, when it's too difficult to express a specific query.

A novel methodology for QoE evaluation in the social network environment is proposed. It provides high applicability for subjective testing of the multimedia services with respect to real usage scenarios. The environment of social networks provides also significant demographic data and ability to contact extremely many test subjects while allows to focus on or filter specific social groups. QoE results for HD internet video services are presented and followed by discussion on their statistical significance.

The best-effort service model of the Internet is unsuitable for streaming applications which require a smooth and flexible packet transmission rate. TCP is unable to provide such a sending rate due to its strict adherence to congestion control. We study the effect of the transport protocol's send buffer size on the performance of streaming media and propose a dynamic send buffer tuning approach which also provides congestion feedback to the application. Simulation results show that this technique improves streaming performance.

HTTP adaptive streaming was introduced with the general idea that user agents interpret a manifest file (describing different representations and segments of the media); whereafter they retrieve the media content using sequential HTTP progressive download operations. MPEG started with the standardization of an HTTP streaming protocol, defining the structure and semantics of a manifest file and additional restrictions and extensions for container formats. At the same time, W3C is working on a specification for addressing media fragments on the Web using Uniform Resource Identifiers. The latter not only defines the URI syntax for media fragment identifiers but also the protocol for retrieving media fragments over HTTP. In this paper, we elaborate on the role of Media Fragment URIs within HTTP adaptive streaming scenarios. First, we elaborate on how different media representations can be addressed by means of Media Fragment URIs, by using track fragments. Additionally, we illustrate how HTTP adaptive streaming is realized relying on the Media Fragments URI retrieval protocol. To validate the presented ideas, we implemented Apple's HTTP Live streaming technique using Media Fragment URIs.

Netflix has been producing a nostalgia subgenre that takes its cues from the visual culture of the past and triggers a form of sentimental longing for the past in the viewer. In shows like The Get Down, Stranger Things, Glow, and Fuller House, narrative elements provoke nostalgia for the ’70s, ’80s, and ’90s. These and other Netflix Originals engage in an aesthetic and politics of viewer reception that projects an image of earlier times and spaces in which the critical historical viewpoint is marginalized in favor of nostos -return—which can also generate retro-futures, the futures that were once imagined in these pasts. Through a critical textual and material analysis of Netflix’s One Day At A Time (ODAAT), this article considers how Netflix capitalizes on a vision of the 1970s as a marketing tactic aimed at attracting a Latina/o audience that revives an older show, creating an emotional atmosphere out of the reception space of fandom itself as viewers’ anxieties about the show’s cancellation and the narrative of saving a show are incorporated into the manipulated aura of the show itself. Originally created by Norman Lear in 1975, this first ODAAT told the story of a divorced working-class white woman from Indianapolis raising strong-willed daughters and of the family’s interactions with the handyman at the building where they lived. Lear revived the show in 2017 and hired writer, actor, editor, and producer Gloria Calderón-Kellet as showrunner and cultural translator. The publicity around the revival leans heavily on the concept that this is a Latina/o remake/reboot/reimagination/twist of the older sitcom. The selling point is to reimagine a show linked to 1970s popular culture through the lens of a 2010s emphasis on diversity. Several deployments of nostalgia produce this effect: the marketing, the fictional in-show narrative, and the real-world storyline produced by the announced possibility of an eventual cancellation of the show that created anxiety among its fans. My interest is to explore whether nostalgia can be deployed as a source of creative renewal and how it functions as a means of critiquing present conditions of production, circulation, and consumption of Latina/o representations.

The power consumption of a streaming-media server can be obtained in real time by using the virtual-instrumentation software described in this paper without using an additional hardware meter. We have built a model to estimate the power consumption from the observation of experimental data that consists of tracking the CPU utilization and detecting the operation parameters of the measured servers. When calculated in real time, the CPU utilization can respond to the dynamic change of the power consumption of the measured servers. The operation parameters represent the hardware configuration of the measured servers. We also propose three methods to obtain these parameters: filledmanually, hardware-revised, and software-revised parameter estimating. We have constructed the virtual-instrumentation software according to this power model to measure the power consumption of the streaming-media server. To facilitate the measurement process, we have also designed a suitable graphic-user interface for it. Our virtual-instrumentation software with three parameterestimating methods has been tested by way of comparison with measurement results obtained by a power meter. The average power values of the hardware-revised method are found to yield mean errors of the estimate within 3%. The mean error of the software-revised method is within 6%. However, the filledmanually method may underestimate the power consumption by as much as 11%.

This paper presents GIMME (General Image Multiview Manipulation Engine), a highly flexible reconfigurable stand-alone mobile two-camera vision platform with stereo-vision capability. GIMME relies on reconfigurable hardware (FPGA) to perform application-specific low to mediumlevel image-processing at video-rate. The Qseven-extension enables additional processing power. Thanks to its compact design, low power consumption and standardized interfaces (power and communication), GIMME is an ideal vision platform for autonomous and mobile robot applications.

We analyze a peer-assisted Video-on-Demand system in which users contribute their upload bandwidth to the redistribution of a video that they are downloading or that they have cached locally. Our target is to characterize the additional bandwidth that servers must supply to immediately satisfy all requests to watch a given video. We develop an approximate fluid model to compute the required server bandwidth in the sequential delivery case, as well as in controlled Bit-Torrent like swarms. Our approach is able to capture several stochastic effects related to peer churn, upload bandwidth heterogeneity, nonstationary traffic conditions, which have not been documented or analyzed before. We provide an analytical methodology to design efficient peer-assisted VoD systems and optimal resource allocation strategies under server capacity constraints.

Due to the explosive growth of the Internet and increasing demand for multimedia information on the web, streaming video over the Internet has received tremendous attention from academia and industry. Transmission of real-time video typically has bandwidth, delay, and loss requirements. However, the current best-effort Internet does not offer any quality of service (QoS) guarantees to streaming video. Furthermore, for video multicast, it is difficult to achieve both efficiency and flexibility. Thus, Internet streaming video poses many challenges. To address these challenges, extensive research has been conducted. This special issue is aimed at dissemination of the contributions in the field of streaming video over the Internet. To introduce this special issue with the necessary background and provide an integral view on this field, we cover six key areas of streaming video. Specifically, we cover video compression, application-layer QoS control, continuous media distribution services, streaming servers, media synchronization mechanisms, and protocols for streaming media. For each area, we address the particular issues and review major approaches and mechanisms. We also discuss the tradeoffs of the approaches and point out future research directions.

In this paper we address the problem of efficient layered video streaming over peer-to-peer networks and we propose a new receiver-driven streaming mechanism. The main design goal of our new layered video requesting policy is to optimize the overall distribution of video streams in terms of reliability and overhead. Since the layered peer-to-peer streaming problem is NP-Hard, we show that the classic approaches widely used in layered P2P streaming systems have some limitations and we propose an optimization technique based on harmony search which aims at increasing the rate of successful data transmissions for the most important video layers, while reducing the protocol overhead and ensuring load balancing among the participating peers. Analytical results have demonstrated that our new requesting policy enhances the streaming of layered video over mesh-based peer-to-peer networks and outperforms classic approaches.

We consider the problem of bit-rate allocation for multiple video users sharing a common transmission channel. Previously, overall quality of multiple users was improved by exploiting relative video complexity. Users with high-complexity video benefit at the expense of video quality reduction for other users with simpler videos. The quality of all users can be improved by collectively allocating the bit rate in a centralized fashion which requires sharing video information with a central controller. In this paper, we present an informationally decentralized bit-rate allocation for multiple users where a user only needs to inform his demand to an allocator. Each user separately calculates his bit-rate demand based on his video complexity and bit-rate price, where the bit-rate price is announced by the allocator. The allocator adjusts the bit-rate price for the next period based on the bit rate demanded by the users and the total available bit-rate supply. Simulation results show that all users improve their quality by the pricing-based decentralized bit-rate allocation method compared with their allocation when acting individually. The results of our proposed method are comparable to the centralized bit-rate allocation.

Traffic sign recognition (TSR) is one of the most important background research topics for enabling autonomous vehicle driving systems. Autonomous driving systems require special handling of input data: there is no time for complex transformations or sophisticated image processing techniques, they need a solid and real-time analysis of a situation. This challenge get more difficult to meetin a city like environment where multiple traffic signs, ads, parking vehicles, pedestrians, and other moving or background objects make the recognition much more difficult. While numerous solutions have been published, solutions are tested on autoways, country-side, or at a very low speed. In this paper, we give a short overview on main problems and known strategies to solve these problems, and we give a general solution to tackle real-time issues in urban traffic sign recognition.

Urban traffic control systems have based their technological infrastructure both on advanced analog close-circuit television systems (CCTV) and point-to-point links, providing difficult-to-scale and very expensive systems. The main goal of an urban traffic monitoring system is to capture, send, play and distribute video information from the streets of a certain city to a management centre where it is processed by different services. Current digitalization process of video networks, and the research carried out in the field of streaming media, has led vendors to present proprietary hardware and software solutions resulting in a strong dependency by their customers. This work presents an open urban traffic control system based in commercial off-the-shelf (COTS) philosophy for hardware and software components, as well as open source and standardized protocols. The existence of open standards for video encoding and protocols for streaming media transmission over IP networks has led to the proposal of such a system. The proposed system is a suitable solution in terms of scalability, cost, interoperability and performance for traffic control systems. Furthermore, its architecture can be easily adapted to other video applications and tools like command and control, surveillance or security systems for military and civilian applications. r

In this paper, a performance comparison of two H.264/SVC-compliant video decoders, Joint Scalable Video Model and Open SVC, is presented. The performance, in terms of time spent to decode a stream, has been compared in PC and Digital Signal Processor (DSP) environments. The performance of the Open SVC decoder running on the PC is between three and eight times better than achieved with the JSVM decoder; while in the DSP environment, the improvement is between five and twelve times. These results show that the Open SVC decoder is more suitable as starting point for the implementation of embedded applications based on DSP 1 .