TRECVID: benchmarking the effectiveness of information retrieval tasks on digital video

Many research groups worldwide are now investigating techniques which can support information retrieval on archives of digital video and as groups move on to implement these techniques they inevitably try to evaluate the performance of their techniques in practical situations. The difficulty with doing this is that there is no test collection or any environment in which the effectiveness of video IR or video IR sub-tasks, can be evaluated and compared. The annual series of TREC exercises has, for over a decade, been benchmarking the effectiveness of systems in carrying out various information retrieval tasks on text and audio and has contributed to a huge improvement in many of these. Two years ago, a track was introduced which covers shot boundary detection, feature extraction and searching through archives of digital video. In this paper we present a summary of the activities in the TREC Video track in 2002 where 17 teams from across the world took part

Sensor nets discover search

In the world of information discovery there are several major trends which are emerging. These include the fact that the nature of search itself is changing because our information needs are themselves becoming more complex and the data volume is increasing. Other trends are that information is increasingly being aggregated, and that search is now becoming information discovery. In this presentation I address a different kind of information source to the usual media, scientific, leisure, and entertainment information we usually consume, whose availability is now upon us, namely data gathered from sensors. This covers both the physical sensors around us which monitor our environment, our wellbeing and our activities, as well as the online sensors which monitor and track things happening elsewhere in the work and to which we have access. These sensor information sources are noisy, errorsome, unpredictable and dynamic, exactly like both our real and our virtual worlds. Several wide-ranging sensor web applications are used to demonstrate the importance of event processing in managing information discovery from the sensor web

The Físchlár digital library: networked access to a video archive of TV news

This paper presents an overview of the Físchlár digital library, a collection of over 300 hours of broadcast TV content which has been indexed to allow searching, browsing and playback of video. The system is in daily use by over 1,500 users on our University campus and is used for teaching and learning, for research, and for entertainment. It is shortly to be made available to University libraries elsewhere in Ireland. The infrastructure we use is a Gigabit ETHERNET backbone and a conventional web browser for searching and browsing video content, with a browser plug-in for streaming video. As well as providing an overview of the system, the paper concentrates on the complimentary navigation techniques of browsing and searching which are supported within Físchlár

So what can we actually do with content-based video retrieval?

In this talk I will give a roller-coaster survey of the state of the art in automatic video analysis, indexing, summarisation, search and browsing as demonstrated in the annual TRECVid benchmarking evaluation campaign. I will concentrate on content-based techniques for video management which form a complement to the dominant paradigm of metadata or tag-based video management and I will use example techniques to illustrate these

Content-based access to digital video: the Físchlár system and the TREC video track

This short paper presents an overview of the Físchlár system - an operational digital library of several hundred hours of video content at Dublin City University which is used by over 1,000 users daily, for a variety of applications. The paper describes how Físchlár operates and the services that it provides for users. Following that, the second part of the paper gives an outline of the TREC Video Retrieval track, a benchmarking exercise for information retrieval from video content currently in operation, summarising the operational details of how the benchmarking exercise is operating

A comparison of score, rank and probability-based fusion methods for video shot retrieval

It is now accepted that the most effective video shot retrieval is based on indexing and retrieving clips using multiple, parallel modalities such as text-matching, image-matching and feature matching and then combining or fusing these parallel retrieval streams in some way. In this paper we investigate a range of fusion methods for combining based on multiple visual features (colour, edge and texture), for combining based on multiple visual examples in the query and for combining multiple modalities (text and visual). Using three TRECVid collections and the TRECVid search task, we specifically compare fusion methods based on normalised score and rank that use either the average, weighted average or maximum of retrieval results from a discrete Jelinek-Mercer smoothed language model. We also compare these results with a simple probability-based combination of the language model results that assumes all features and visual examples are fully independent

Spatially augmented audio delivery: applications of spatial sound awareness in sensor-equipped indoor environments

Current mainstream audio playback paradigms do not take any account of a user's physical location or orientation in the delivery of audio through headphones or speakers. Thus audio is usually presented as a static perception whereby it is naturally a dynamic 3D phenomenon audio environment. It fails to take advantage of our innate psycho-acoustical perception that we have of sound source locations around us. Described in this paper is an operational platform which we have built to augment the sound from a generic set of wireless headphones. We do this in a way that overcomes the spatial awareness limitation of audio playback in indoor 3D environments which are both location-aware and sensor-equipped. This platform provides access to an audio-spatial presentation modality which by its nature lends itself to numerous cross-dissiplinary applications. In the paper we present the platform and two demonstration applications