Temporal hybridity: Mixing live video footage with instant replay in real time

Copyright @ 2010 ACMIn this paper we explore the production of streaming media that involves live and recorded content. To examine this, we report on how the production practices and process are conducted through an empirical study of the production of live television, involving the use of live and non-live media under highly time critical conditions. In explaining how this process is managed both as an individual and collective activity, we develop the concept of temporal hybridity to explain the properties of these kinds of production system and show how temporally separated media are used, understood and coordinated. Our analysis is examined in the light of recent developments in computing technology and we present some design implications to support amateur video production.The research was partly made possible by a grant from the Swedish Governmental Agency for Innovation Systems to the Mobile Life VinnExcellence Center, in partnership with SonyEricsson, Ericsson, Microsoft Research, Nokia Research, TeliaSonera and the City of Stockholm

Spott : on-the-spot e-commerce for television using deep learning-based video analysis techniques

Spott is an innovative second screen mobile multimedia application which offers viewers relevant information on objects (e.g., clothing, furniture, food) they see and like on their television screens. The application enables interaction between TV audiences and brands, so producers and advertisers can offer potential consumers tailored promotions, e-shop items, and/or free samples. In line with the current views on innovation management, the technological excellence of the Spott application is coupled with iterative user involvement throughout the entire development process. This article discusses both of these aspects and how they impact each other. First, we focus on the technological building blocks that facilitate the (semi-) automatic interactive tagging process of objects in the video streams. The majority of these building blocks extensively make use of novel and state-of-the-art deep learning concepts and methodologies. We show how these deep learning based video analysis techniques facilitate video summarization, semantic keyframe clustering, and (similar) object retrieval. Secondly, we provide insights in user tests that have been performed to evaluate and optimize the application's user experience. The lessons learned from these open field tests have already been an essential input in the technology development and will further shape the future modifications to the Spott application

CHORUS Deliverable 2.1: State of the Art on Multimedia Search Engines

Based on the information provided by European projects and national initiatives related to multimedia search as well as domains experts that participated in the CHORUS Think-thanks and workshops, this document reports on the state of the art related to multimedia content search from, a technical, and socio-economic perspective. The technical perspective includes an up to date view on content based indexing and retrieval technologies, multimedia search in the context of mobile devices and peer-to-peer networks, and an overview of current evaluation and benchmark inititiatives to measure the performance of multimedia search engines. From a socio-economic perspective we inventorize the impact and legal consequences of these technical advances and point out future directions of research

Learning to Generate Posters of Scientific Papers

Researchers often summarize their work in the form of posters. Posters provide a coherent and efficient way to convey core ideas from scientific papers. Generating a good scientific poster, however, is a complex and time consuming cognitive task, since such posters need to be readable, informative, and visually aesthetic. In this paper, for the first time, we study the challenging problem of learning to generate posters from scientific papers. To this end, a data-driven framework, that utilizes graphical models, is proposed. Specifically, given content to display, the key elements of a good poster, including panel layout and attributes of each panel, are learned and inferred from data. Then, given inferred layout and attributes, composition of graphical elements within each panel is synthesized. To learn and validate our model, we collect and make public a Poster-Paper dataset, which consists of scientific papers and corresponding posters with exhaustively labelled panels and attributes. Qualitative and quantitative results indicate the effectiveness of our approach.Comment: in Proceedings of the 30th AAAI Conference on Artificial Intelligence (AAAI'16), Phoenix, AZ, 201

CHORUS Deliverable 4.3: Report from CHORUS workshops on national initiatives and metadata

Minutes of the following Workshops: • National Initiatives on Multimedia Content Description and Retrieval, Geneva, October 10th, 2007. • Metadata in Audio-Visual/Multimedia production and archiving, Munich, IRT, 21st – 22nd November 2007 Workshop in Geneva 10/10/2007 This highly successful workshop was organised in cooperation with the European Commission. The event brought together the technical, administrative and financial representatives of the various national initiatives, which have been established recently in some European countries to support research and technical development in the area of audio-visual content processing, indexing and searching for the next generation Internet using semantic technologies, and which may lead to an internet-based knowledge infrastructure. The objective of this workshop was to provide a platform for mutual information and exchange between these initiatives, the European Commission and the participants. Top speakers were present from each of the national initiatives. There was time for discussions with the audience and amongst the European National Initiatives. The challenges, communalities, difficulties, targeted/expected impact, success criteria, etc. were tackled. This workshop addressed how these national initiatives could work together and benefit from each other. Workshop in Munich 11/21-22/2007 Numerous EU and national research projects are working on the automatic or semi-automatic generation of descriptive and functional metadata derived from analysing audio-visual content. The owners of AV archives and production facilities are eagerly awaiting such methods which would help them to better exploit their assets.Hand in hand with the digitization of analogue archives and the archiving of digital AV material, metadatashould be generated on an as high semantic level as possible, preferably fully automatically. All users of metadata rely on a certain metadata model. All AV/multimedia search engines, developed or under current development, would have to respect some compatibility or compliance with the metadata models in use. The purpose of this workshop is to draw attention to the specific problem of metadata models in the context of (semi)-automatic multimedia search

Multimedia delivery in the future internet

The term “Networked Media” implies that all kinds of media including text, image, 3D graphics, audio and video are produced, distributed, shared, managed and consumed on-line through various networks, like the Internet, Fiber, WiFi, WiMAX, GPRS, 3G and so on, in a convergent manner [1]. This white paper is the contribution of the Media Delivery Platform (MDP) cluster and aims to cover the Networked challenges of the Networked Media in the transition to the Future of the Internet. Internet has evolved and changed the way we work and live. End users of the Internet have been confronted with a bewildering range of media, services and applications and of technological innovations concerning media formats, wireless networks, terminal types and capabilities. And there is little evidence that the pace of this innovation is slowing. Today, over one billion of users access the Internet on regular basis, more than 100 million users have downloaded at least one (multi)media file and over 47 millions of them do so regularly, searching in more than 160 Exabytes1 of content. In the near future these numbers are expected to exponentially rise. It is expected that the Internet content will be increased by at least a factor of 6, rising to more than 990 Exabytes before 2012, fuelled mainly by the users themselves. Moreover, it is envisaged that in a near- to mid-term future, the Internet will provide the means to share and distribute (new) multimedia content and services with superior quality and striking flexibility, in a trusted and personalized way, improving citizens’ quality of life, working conditions, edutainment and safety. In this evolving environment, new transport protocols, new multimedia encoding schemes, cross-layer inthe network adaptation, machine-to-machine communication (including RFIDs), rich 3D content as well as community networks and the use of peer-to-peer (P2P) overlays are expected to generate new models of interaction and cooperation, and be able to support enhanced perceived quality-of-experience (PQoE) and innovative applications “on the move”, like virtual collaboration environments, personalised services/ media, virtual sport groups, on-line gaming, edutainment. In this context, the interaction with content combined with interactive/multimedia search capabilities across distributed repositories, opportunistic P2P networks and the dynamic adaptation to the characteristics of diverse mobile terminals are expected to contribute towards such a vision. Based on work that has taken place in a number of EC co-funded projects, in Framework Program 6 (FP6) and Framework Program 7 (FP7), a group of experts and technology visionaries have voluntarily contributed in this white paper aiming to describe the status, the state-of-the art, the challenges and the way ahead in the area of Content Aware media delivery platforms