User-generated Video Content Research Articles

Predicting the Quality of Compressed Videos With Pre-Existing Distortions.

Because of the increasing ease of video capture, many millions of consumers create and upload large volumes of User-Generated-Content (UGC) videos to social and streaming media sites over the Internet. UGC videos are commonly captured by naive users having limited skills and imperfect techniques, and tend to be afflicted by mixtures of highly diverse in-capture distortions. These UGC videos are then often uploaded for sharing onto cloud servers, where they are further compressed for storage and transmission. Our paper tackles the highly practical problem of predicting the quality of compressed videos (perhaps during the process of compression, to help guide it), with only (possibly severely) distorted UGC videos as references. To address this problem, we have developed a novel Video Quality Assessment (VQA) framework that we call 1stepVQA (to distinguish it from two-step methods that we discuss). 1stepVQA overcomes limitations of Full-Reference, Reduced-Reference and No-Reference VQA models by exploiting the statistical regularities of both natural videos and distorted videos. We also describe a new dedicated video database, which was created by applying a realistic VMAF-Guided perceptual rate distortion optimization (RDO) criterion to create realistically compressed versions of UGC source videos, which typically have pre-existing distortions. We show that 1stepVQA is able to more accurately predict the quality of compressed videos, given imperfect reference videos, and outperforms other VQA models in this scenario.

Character-Oriented Video Summarization With Visual and Textual Cues

With the booming of content “re-creation” in social media platforms, character-oriented video summary has become a crucial form of user-generated video content. However, artificial extraction could be time-consuming with high missing rate, while traditional techniques on person search may incur heavy burden of computing resources. At the same time, in social media platforms, videos are usually accompanied with rich textual information, e.g., subtitles or bullet-screen comments which provide the multi-view description of videos. Thus, there exists a potential to leverage textual information to enhance the character-oriented video summarization. To that end, in this paper, we propose a novel framework for jointly modeling visual and textual information. Specifically, we first locate characters indiscriminately through detection methods, and then identify these characters via re-identification to extract potential key-frames, in which appropriate source of textual information will be automatically selected and integrated based on the features of specific frame. Finally, key-frames will be aggregated as the character-oriented summarization. Experiments on real-world data sets validate that our solution outperforms several state-of-the-art baselines on both person search and summarization tasks, which prove the effectiveness of our solution on the character-oriented video summarization problem.

Policing the “Sensible” in the Era of YouTube: Urban Villages and Racialized Subjects in Delhi

This article attends to the ways in which user-generated video content presumed destined for online social media circulation polices the sensible and, in turn, is policed because of its capacity to reveal the messy, turbulent politics of the everyday. Focusing on an incident that targeted African students and entrepreneurs residing in Delhi, the article argues that the policing of user-generated audio-visual content of unfolding events in this milieu reveals a politics of the sensible that imagines digital circulation beyond national borders as a key site of contestation and that pushes us to reconsider simplistic ideas that valorize the democratization of representation as an interruption of the social order in one sociotemporal scale.

Critical link-aware P2P search for internet videos in semantic overlay network

Search is fundamentally important for Internet video systems, especially for user generated content (UGC) video systems (like YouTube and YouKu). Currently, these systems rely on centralized servers for video search. In this paper, we study the P2P (Peer-to-Peer) search in UGC video systems, to achieve low latency and low overhead search. To this end, we propose to build semantic overlays for users in UGC video systems. Each node (user) designates most of its connections to link with semantically relevant nodes, resulting in an overlay network with large but tight clusters. A critical link-aware search algorithm (CLA) is further proposed for query forwarding. CLA prefers loose connections that are critical for the connectivity of semantic clusters to forward queries if local clusters are not the relevant ones. The algorithm enables queries to quickly reach the semantically relevant clusters, while large clusters make it possible that queries are satisfied within the relevant clusters once reaching them. We adopt the Bloom filter to reduce maintenance cost. Finally, we use the YouKu trace for experiments. The results show the efficiency and effectiveness of CLA.

User-Generated Captions: From Hackers, to the Disability Digerati, to Fansubbers

User-Generated Captions: From Hackers, to the Disability Digerati, to Fansubbers

The global television news agencies and their handling of user generated content video from Syria

This article examines the role that the global television news agencies play in the handling of user generated content (UGC) video from Syria. In the almost complete absence of independent journalists, Reuters, Associated Press and Agence France-Presse are sourcing citizen videos from YouTube channels and passing it on to their clients. This article examines the verification processes that the agencies undertake to check on the veracity of this material and asks whether the agencies have abandoned independent journalism to activists. This article provides a comparative analysis of two months’ worth of UGC videos from Syria that were broadcast by the global news agencies after Russia joined the bombing campaign in Syria in late 2015. It analyses the content, verification processes and information that the agencies give their clients about this material. Through interviews with senior editors from the three organisations, questions of certainty versus probability are explored, along with ethical arguments about propaganda versus information transparency. The global news agencies are the engine drivers of international news coverage and their decisions and interpretation feed directly into the media ecology of mainstream and then alternative media.

Social-aware video delivery: challenges, approaches, and directions

We have recently witnessed the convergence of online social network services and online video services: users import videos from content sharing sites, and propagate them along the social connections by re-sharing them. Such social behaviors have dramatically reshaped how videos are disseminated, and users are now actively engaged as part of the social ecosystem, rather than being passive consumers. Despite the increasingly abundant bandwidth and computation resources, the ever increasing data volume of user generated video content and the boundless coverage of socialized sharing have presented unprecedented challenges. This article first presents the challenges in social-aware video delivery. Then we present a principal framework for social-aware video delivery and a state-of-the-art overview of approaches. Moreover, we identify the unique characteristics of social-aware video access and social content propagation, and reveal the design of individual modules and their integration toward enhancing users' experience in the social network context. Finally, we discuss future research directions.

Joint optimization of admission control and rate adaptation for video sharing over multirate wireless community cloud

Emerging wireless community cloud enables usergenerated video content to be shared and consumed in a social context. However, the nature of shared wireless medium and time-varying channels seriously limits the quality of service (QoS), partially owing to the lack of mechanisms for effectively utilizing multi-rate channel resources. In this paper, the joint optimization of admission control and rate adaptation is proposed, resulting in a bandwidth-aware rate-adaptive admission control (BRAC) scheme to provide bandwidth guarantee for sharing social multimedia contents. The analytical approach leads to the following major contributions: (1) a bandwidth-aware rate selection (BRS) algorithm to optimally meet the bandwidth requirement of the data session and channel conditions at the physical layer; (2) a routing-coupled rate adaption and admission control algorithm to admit data sessions with bandwidth guarantee. Moreover, extensive numerical simulations suggest that BRAC is efficient and effective in meeting the bandwidth requirements for sharing social multimedia contents. These insights will shed light on communication system implementation for multimedia content sharing over multirate wireless community cloud.

QoE-Based Cross-Layer Optimization for Uplink Video Transmission

We study the problem of resource-efficient uplink distribution of user-generated video content over fourth-generation mobile networks. This is challenged by (1) the capacity-limited and time-variant uplink channel, (2) the resource-hungry upstreamed videos and their dynamically changing complexity, and (3) the different playout times of the video consumers. To address these issues, we propose a systematic approach for quality-of-experience (QoE)-based resource optimization and uplink transmission of multiuser generated video content. More specifically, we present an analytical model for distributed scalable video transmission at the mobile producers which considers these constraints. This is complemented by a multiuser cross-layer optimizer in the mobile network which determines the transmission capacity for each mobile terminal under current cell load and radio conditions. Both optimal and low-complexity solutions are presented. Simulation results for LTE uplink transmission show that significant gains in perceived video quality can be achieved by our cross-layer resource optimization scheme. In addition, the distributed optimization at the mobile producers can further improve the user experience across the different types of video consumers.

YouTube stickiness: the needs, personal, and environmental perspective

Purpose – Many video sharing sites (e.g. YouTube, Vimeo, and Break) host user-generated video content in the hopes of attracting viewers and thus profits. Therefore, continuous use and video sharing behavior on the part of site users is critical to the continue enjoyment of other users and to the video service providers business. The purpose of this paper is to provide an improved understanding of what motivates internet users to share videos and spend more time on video sharing web sites. Design/methodology/approach – The authors propose a research model based on Uses and Gratification Theory and on Social Cognitive Theory, incorporating key determinants of web site stickiness. An online survey instrument was developed to gather data, and 265 questionnaires were used to test the relationships in the model. Findings – The causal model was validated using SmartPLS 2.0, and 14 out of 18 study hypotheses were supported. The results indicated that continuance motivation and sharing behavior were important antecedents of YouTube stickiness and mediated the influence of need, personal, and environmental factors. Practical implications – The proposed framework can be used by online video service providers to develop a platform that satisfies user needs and to enhance sharing intention. Originality/value – The study provides a comprehensive framework of the antecedents and effects of continuance motivation and sharing behavior on video sharing web sites.

Down the (White) Rabbit Hole: The Extreme Right and Online Recommender Systems

In addition to hosting user-generated video content, YouTube provides recommendation services, where sets of related and recommended videos are presented to users, based on factors such as co-visitation count and prior viewing history. This article is specifically concerned with extreme right (ER) video content, portions of which contravene hate laws and are thus illegal in certain countries, which are recommended by YouTube to some users. We develop a categorization of this content based on various schema found in a selection of academic literature on the ER, which is then used to demonstrate the political articulations of YouTube’s recommender system, particularly the narrowing of the range of content to which users are exposed and the potential impacts of this. For this purpose, we use two data sets of English and German language ER YouTube channels, along with channels suggested by YouTube’s related video service. A process is observable whereby users accessing an ER YouTube video are likely to be recommended further ER content, leading to immersion in an ideological bubble in just a few short clicks. The evidence presented in this article supports a shift of the almost exclusive focus on users as content creators and protagonists in extremist cyberspaces to also consider online platform providers as important actors in these same spaces.

Video interaction: a research agenda

The topic of this special issue is the broadened use of video and the need to articulate a research agenda that addresses its new opportunities and challenges. This agenda, which we argue should be labelled ‘‘video interaction,’’ is influenced by both emerging practices and technical developments. In the widest sense, we refer to video interaction as a research area concerned with emerging technologies and social practices in an increasingly flattened hierarchy between, on the one hand, what used to be a well-defined group of production professionals, and on the other hand, the masses of passive viewers of the same media. This transition happens at the same time as video traffic has become the bulk of data communication on the Internet [2]. The same shift is now happening in mobile data. Cisco reports that mobile video traffic exceeded 50 % for the first time in 2012. They predict that the numbers for video will continue to increase dramatically. In 5 years, the amount of mobile video data is projected to increase 16-fold, ending up at over two-thirds of the entire data traffic [12]. Obviously, downloading and streaming of movies and TV series are the big drivers in this development, but there are a number of other things happening that warrant a new approach to understanding interaction with video content, beyond the notion of the user as a viewer in the traditional sense. The practices surrounding moving image technology are now transcending consumption of traditional media, and becoming integrated with other interactive services and social media [2]. In this massive growth of video online, there are a number of parallel trends regarding how video is consumed, produced, shared, and interacted with that we argue require a re-conceptualisation of the area. In the following, we will map out the changed use of video and then analyze its opportunities and challenges, and explain the need for a coherent research approach to video interaction. In particular, the trends we want to align are a shift to user-generated video content and to mobile technology, as well as a continuation of the trend of increased interaction in viewing (iTV). First, new ways of producing video content has emerged, enabled by the availability of cheap production tools and high bandwidth communication networks. It emerged with the use of both analogue and digital video cameras for consumers, and continued with video recording facilities on mobile phones [30]. The cost and effort of sharing and distributing the content have also diminished with the expansion of the fixed Internet. Live video production is now on the verge of the same kind of democratization of means of production and broader adoption by nonprofessional users. Through highly visible examples such as live broadcasts from the Arabic Spring and other news events around the world, as well as more mundane practices of broadcasting from university lectures and local events, live video has shown potential for communicating and sharing experiences with remote viewers. Second, we see an expansion of services that utilize mobile technology in a broad sense, and that are catering to O. Juhlin G. Zoric (&) A. Engstrom Stockholm, Sweden e-mail: goga@mobilelifecentre.org

Storisphere: from TV watching to community story telling

Conventional television services have been increasingly challenged by the more interactive and user-centric video sharing applications. With the growing popularity of social networks and video services, users are becoming the editors and broadcasters of their own stories. User-generated video content, which provides unique perspectives from individuals, is likely to be the new medium to complement professional broadcast TV for story sharing, especially in user communities of specific interest. We have developed Storisphere to provide a web-based collaborative video content workspace for members of a community to compose and share video stories, using desktop or mobile devices. Storisphere is currently being evaluated for video storytelling by various user communities.

Social Connections in User-Generated Content Video Systems: Analysis and Recommendation

User-generated content (UGC) video systems by definition heavily depend on the input of their community of users and their social interactions for video diffusion and opinion sharing. Nevertheless, we show in this paper, through measurement and analysis of YouKu, the most popular UGC video system in China, that the social connectivity of its users is very low. These observations are consistent with what was reported about YouTube in previous works. As a UGC system can achieve a larger audience through improved connectivity, our findings motivate us to propose a mean to enhance the users' connectivity by taking benefit of friend recommendation. To this end, we assess two similarity metrics based on users' interests that are derived from their uploads and favorites tagging of videos, to evaluate the interest similarity between friends. The results consistently show that friends share to a great extent common interests. Two friend recommendation algorithms are then proposed. The algorithms use public information provided by users to suggest potential friends with similar interests as measured by the similarity metrics. Experiments on our gathered YouKu dataset demonstrate that the social connectivity can be greatly enhanced by our friend proposition set and that users can access a larger set of interesting videos through the recommendations.

Engaging Viewers Through the Connected Studio: Virtual Participation in TV Programs

In recent years, since broadband communication networks have become widely available, it is possible for ordinary viewers to access video content easily at any time or place with the use of services that deliver video content in a wide diversity of genres. Content delivery services that use user-generated video content have also become popular [1][3]. As technology supports the creation of video content, video editing systems [4], computer graphics (CG) software [5], and the like are being put to practical use. However, technical expertise is needed to use these tools. Furthermore, these tools expect the content creators to take care of key directorial and production roles, such as deciding how the video should be shot, what sort of composition to use, and how to present this content to the viewers. Specialized skills and experiences are needed for these tasks. For ordinary people with no special skills or experiences, the creation of video content can be difficult.

Multimodal Semantics Extraction from User-Generated Videos

User-generated video content has grown tremendously fast to the point of outpacing professional content creation. In this work we develop methods that analyze contextual information of multiple user-generated videos in order to obtain semantic information about public happenings (e.g., sport and live music events) being recorded in these videos. One of the key contributions of this work is a joint utilization of different data modalities, including such captured by auxiliary sensors during the video recording performed by each user. In particular, we analyze GPS data, magnetometer data, accelerometer data, video- and audio-content data. We use these data modalities to infer information about the event being recorded, in terms of layout (e.g., stadium), genre, indoor versus outdoor scene, and the main area of interest of the event. Furthermore we propose a method that automatically identifies the optimal set of cameras to be used in a multicamera video production. Finally, we detect the camera users which fall within the field of view of other cameras recording at the same public happening. We show that the proposed multimodal analysis methods perform well on various recordings obtained in real sport events and live music performances.

Categorising YouTube

This article provides a genre analytical approach to creating a typology of the User Generated Content (UGC) of YouTube. The article investigates the construction of navigationprocesses on the YouTube website. It suggests a pragmatic genre approach that is expanded through a focus on YouTube’s technological affordances. Through an analysis of the different pragmatic contexts of YouTube, it is argued that a taxonomic understanding of YouTube must be analysed in regards to the vacillation of a user-driven bottom-up folksonomy and a hierarchical browsing system that emphasises a culture of competition and which favours the already popular content of YouTube. With this taxonomic approach, the UGC videos are registered and analysed in terms of empirically based observations. The article identifies various UGC categories and their principal characteristics. Furthermore, general tendencies of the UGC within the interacting relationship of new and old genres are discussed. It is argued that the utility of a conventional categorical system is primarily of analytical and theoretical interest rather than as a practical instrument.

Design and implementation of geo-tagged video search framework

User generated video content is experiencing significant growth which is expected to continue and further accelerate. As an example, users are currently uploading 20 h of video per minute to YouTube. Making such video archives effectively searchable is one of the most critical challenges of multimedia management. Current search techniques that utilize signal-level content extraction from video struggle to scale. Here we present a framework based on the complementary idea of acquiring sensor streams automatically in conjunction with video content. Of special interest are geographic properties of mobile videos. The meta-data from sensors can be used to model the coverage area of scenes as spatial objects such that videos can effectively, and on a large scale, be organized, indexed and searched based on their field-of-views. We present an overall framework that is augmented with our design and implementation ideas to illustrate the feasibility of this concept of managing geo-tagged video.

Analyzing the Video Popularity Characteristics of Large-Scale User Generated Content Systems

User generated content (UGC), now with millions of video producers and consumers, is re-shaping way people watch video and TV. In particular, UGC sites are creating new viewing patterns and social interactions, empowering users to be more creative, and generating new business opportunities. Compared to traditional video-on-demand (VoD) systems, UGC services allow users to request videos from a potentially unlimited selection in an asynchronous fashion. To better understand impact of UGC services, we have analyzed world's largest UGC VoD system, YouTube, and a popular similar system in Korea, Daum Videos. In this paper, we first empirically show how UGC services are fundamentally different from traditional VoD services. We then analyze intrinsic statistical properties of UGC popularity distributions and discuss opportunities to leverage latent demand for niche videos (or so-called the Long Tail potential), which is not reached today due to information filtering or other system scarcity distortions. Based on traces collected across multiple days, we study popularity lifetime of UGC videos and relationship between requests and video age. Finally, we measure level of content aliasing and illegal content in system and show problems aliasing creates in ranking video popularity accurately. The results presented in this paper are crucial to understanding UGC VoD systems and may have major commercial and technical implications for site administrators and content owners.

Separating the Sony Sheep from the Grokster Goats: Reckoning the Future Business Plans of Copyright-Dependent Technology Entrepreneurs

U.S. and many other national copyright systems have by statute or caselaw (or both) established rules engaging or excusing liability for facilitating (or, in commonwealth countries, authorizing) copyright infringement. Taken as a group, they share a goal of insulating the innovator whose technology happens, but was not intended, to enable its adopters to make unlawful copies or communications of protected works. The more infringement becomes integrated into the innovator's business plan, however, the less likely the entrepreneur is to persuade a court of the neutrality of its venture. The US Supreme Court's 2005 decision in MGM v Grokster, established that businesses built from the start on inducing infringement will be held liable; judges will frown on drawing one's start-up capital from other people's copyrights. Thus, the inferences entrepreneurs may draw from the Court's elucidation of the elements of inducement may advise pro-active measures to prevent infringement from becoming a business asset. As a result, even businesses not initially built on infringement, but in which infringement comes to play an increasingly profitable part, may find themselves liable unless they take good faith measures to forestall infringements. This article addresses the evolution of the U.S.'s judge-made rules of secondary liability for copyright infringement, and the possible emergence of an obligation of good faith efforts to avoid infringement. The recent announcements of inter-industry for User Generated Services and of complementary Fair Use Principles for User-Generated Video Content suggest that proactive avoidance measures may become a matter of best practice. The article then turns to the statutory regime of safe harbors established for certain Internet service providers and considers whether the statute insulates entrepreneurs who would have been held derivatively liable under common law norms. Finally, the article compares the U.S. developments with recent French decisions holding the operators of user-generated content and social networking websites liable for their customers' unauthorized posting of copyrighted works.