20,397 research outputs found

    Indexing Multimedia for the Internet

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

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    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

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

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    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

    CHORUS Deliverable 4.5: Report of the 3rd CHORUS Conference

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    The third and last CHORUS conference on Multimedia Search Engines took place from the 26th to the 27th of May 2009 in Brussels, Belgium. About 100 participants from 15 European countries, the US, Japan and Australia learned about the latest developments in the domain. An exhibition of 13 stands presented 16 research projects currently ongoing around the world

    Augmenting conversations through context-aware multimedia retrieval based on speech recognition

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    Future’s environments will be sensitive and responsive to the presence of people to support them carrying out their everyday life activities, tasks and rituals, in an easy and natural way. Such interactive spaces will use the information and communication technologies to bring the computation into the physical world, in order to enhance ordinary activities of their users. This paper describes a speech-based spoken multimedia retrieval system that can be used to present relevant video-podcast (vodcast) footage, in response to spontaneous speech and conversations during daily life activities. The proposed system allows users to search the spoken content of multimedia files rather than their associated meta-information and let them navigate to the right portion where queried words are spoken by facilitating within-medium searches of multimedia content through a bag-of-words approach. Finally, we have studied the proposed system on different scenarios by using vodcasts in English from various categories, as the targeted multimedia, and discussed how it would enhance people’s everyday life activities by different scenarios including education, entertainment, marketing, news and workplace

    Image featuring for retrieval of multimedia documents

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    The utilization of massive multimedia documents collections, such as multimedia documents in the global Internet, needs search engines which can rank using both text and image evidence. Massive size and (dynamic) nature of collection can make manual indexing prohibitively expensive in such situations. Traditional search engines utilize only text components of multimedia documents. But there are information needs, which require the utilization of image evidence. In this paper, we investigate image-feature for large and heterogeneous collections. Both the nature and complexities of information needs are key elements for an effective retrieval. Retrieval needs that depend on perceptual similarities (as found in art galleries, building architecture) require the utilization of visual cues. In such situations, the retrieval of multimedia document based on image ranking can provide higher effectiveness. Experimental results show that effectiveness of ranking based on image feature can be higher where perceptual similarities are key elements for retrieval than the retrieval effectiveness of algorithms based on text ranking algorithms <br /
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