Searching for relevant webpages and following hyperlinks to related content is a widely accepted and effective approach to information seeking on the textual web. Existing work on multimedia information retrieval has focused on search for individual relevant items or on content linking without specific attention to search results. We describe our research exploring integrated multimodal search and hyperlinking for multimedia data. Our investigation is based on the MediaEval 2012 Search and Hyperlinking task. This includes a known-item search task using the Blip10000 internet video collection, where automatically created hyperlinks link each relevant item to related items within the collection. The search test queries and link assessment for this task was generated using the Amazon Mechanical Turk crowdsourcing platform. Our investigation examines a range of alternative methods which seek to address the challenges of search and hyperlinking using multimodal approaches. The results of our experiments are used to propose a research agenda for developing effective techniques for search and hyperlinking of multimedia content.

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Abstract. News production is characterized by a complex and dynamic workflow, in which it is important to produce and broadcast reliable news as fast as possible. In this process, the efficient retrieval of previously broadcasted news items is important, both for gathering background information and for reuse of footage in new reports. This paper discusses how the quality of descriptive metadata of news items can be optimized, by collecting data generated during news production. Starting from a description of the news production process of the Flemish public service broadcaster in Belgium (VRT), information systems containing valuable metadata are identified. Subsequently, we present a data model that uniformly represents the available information generated during news production. This data model is then implemented using Semantic Web technologies. Further, we describe how other valuable data sets, present in the Semantic Web, are connected to the data model, enabling semantic search operations.

The current multimedia landscape is characterized by a significant heterogeneity in terms of coding and delivery formats, usage environments, and user preferences. This paper introduces a transparent multimedia content adaptation and delivery approach, i.e., model-driven content adaptation and delivery. It is based on a model that takes into account the structural metadata, semantic metadata, and scalability information of media bitstreams. Further, a format-independent multimedia packaging method is proposed based on this model for media bitstreams and MPEG-B BSDL. Thus, multimedia packaging is obtained by encapsulating the selected and adapted structural metadata within a specific delivery format. This packaging process is implemented using XML transformation filters and MPEG-B BSDL. To illustrate this format-independent packaging technique, we apply it to three packaging formats: RTP, MP4, and Ogg.

The current heterogeneity in networks and devices demands for a high degree of flexibility in IPTV systems for digital television. A scalable video coding scheme (in this paper we focus on H.264/AVC's scalable video coding extension SVC) accommodates this flexibility from the coding point of view. Because the IP-based network delivery chain in IPTV systems may suffer from packet loss (having a severe impact on the visual quality) it is necessary to provide means for error concealment. In this paper we propose a novel method that performs adaptation on impaired SVC bitstreams so that the resulting adapted bitstream is compliant to the SVC specification and that the reconstruction result at the decoder is equivalent compared to the approach where the error concealment is implemented in the decoder itself. The adapted bitstreams have a significantly higher visual quality while our approach does not require any modification to existing SVC-compliant decoders. The results of several experiments show that the proposed method is extremely fast (over 900 frames/s) and that it introduces a negligible overhead in terms of bit rate (ca. 0.02%)