Video Content Foraging

Houten, Ynze van; Schuurman, Jan Gerrit; Verhagen, Pleunes Willem

doi:10.1007/978-3-540-27814-6_6

Cited by 4 publications

(3 citation statements)

References 14 publications

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“…A second research area for the near future is the analysis of people's search behaviour, for example, using Information Foraging Theory. Evaluations in the domain of retrieval provide evidence that browsing is an important mode for users examining (video) collections (Savolainen and Kari 2006;Van Houten 2009). The Sound and Vision video retrieval system should support this type of interaction, based on available metadata, visual features and using vocabularies; technologies used in MuNCH.…”

Section: Discussionmentioning

confidence: 99%

A Multidisciplinary Approach to Unlocking Television Broadcast Archives

Hollink¹,

Schreiber²,

Huurnink³

et al. 2009

Interdisciplinary Science Reviews

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Audiovisual material is a vital component of the world's heritage but it remains diffi cult to access. With the Netherlands Institute for Sound and Vision as one of its partners, the MuNCH project aims to investigate new methods for improving access to a wide range of audiovisual documents. MuNCH brings together three research fi elds: multimedia analysis, language technology and semantic technologies.Within the MuNCH project, we have investigated several combinations of these fi elds. We have compared text matching, ontology querying, and semantic visual querying as methods to translate a multimedia query to the vocabulary of the retrieval system. In addition, we have investigated how users make such a translation, and have used this as a benchmark to create automatic methods. We have used multimedia technology to automatically detect objects and scenes as they occur in video, and made use of language technology to exploit automatic transcriptions of speech. We have enriched the Sound and Vision thesaurus that is used to annotate the TV programmes in order to provide a user with a wider range of search results.In order to verify the results of the project against real user needs, MuNCH has participated in the creation of a logging system which monitors the usage of the Sound and Vision catalogue system. Insights in the needs of real users will be used as input for all three of MuNCH's research strands.keywords Multimedia, Retrieval, Content-based image retrieval, Semantic web, Language technology, User queries 254 LAURA HOLLINK et al.

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Section: Discussionmentioning

confidence: 99%

A Multidisciplinary Approach to Unlocking Television Broadcast Archives

Hollink¹,

Schreiber²,

Huurnink³

et al. 2009

Interdisciplinary Science Reviews

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“…Due to the recent nature of automatic retrieval systems, not much is known about the effectiveness of browsing interfaces for video. Van Houten et al presented new ideas for a browsing interface in [24]. It would also be interesting to compare the results of an interactive video retrieval system to sequential scanning of shots in the dataset for a fixed amount of time.…”

Section: Browsingmentioning

confidence: 99%

Assessing user behaviour in news video retrieval

Hollink

Nguyen

Koelma

et al. 2005

IEE Proc., Vis. Image Process.

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Abstract. In this paper we present the results of a study in which we assess search behaviour of people querying a news archive using an interactive video retrieval system. 242 Search sessions by 39 participants on 24 topics were analysed. Before, during and after the study, participants filled in questionnaires about their expectations of a search. The questionnaire data, logged user actions on the system, queries formulated by users, and a quality measure of each search were studied. The results of the study show that topics concerning 'specific' people or objects were better retrieved than topics concerning 'general' objects and scenes. Users were able to estimate the overall quality of a search but did not know when the optimal result was reached within the search process. Analysis of the results at various stages in the retrieval process suggests that retrieval based on transcriptions of the speech in video data adds more to the average precision of the result than content-based image retrieval based on low-level visual features. The latter is particularly useful in providing the user with an overview of the dataset and thus an indication of the success of a search. Based on the results we discuss implications for the design of user interfaces of video retrieval systems.

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“…Audio-visual content is not restricted to entertainment, but includes also video lectures, instructional videos, interviews, documentaries and so on. Users in many cases do not watch these videos linearly but watch just selected fragments ( [17]). Thus we need methods to browse and search within a video ( [18]) and to find the relevant parts of a video.…”

Section: Introductionmentioning

confidence: 99%

Comparing segmentation strategies for efficient video passage retrieval

Wartena

2012

2012 10th International Workshop on Content-Based Multimedia Indexing (CBMI)

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We compare the effect of different text segmentation strategies on speech based passage retrieval of video. Passage retrieval has mainly been studied to improve document retrieval and to enable question answering. In these domains best results were obtained using passages defined by the paragraph structure of the source documents or by using arbitrary overlapping passages. For the retrieval of relevant passages in a video, using speech transcripts, no author defined segmentation is available. We compare retrieval results from 4 different types of segments based on the speech channel of the video: fixed length segments, a sliding window, semantically coherent segments and prosodic segments. We evaluated the methods on the corpus of the MediaEval 2011 Rich Speech Retrieval task. Our main conclusion is that the retrieval results highly depend on the right choice for the segment length. However, results using the segmentation into semantically coherent parts depend much less on the segment length. Especially, the quality of fixed length and sliding window segmentation drops fast when the segment length increases, while quality of the semantically coherent segments is much more stable. Thus, if coherent segments are defined, longer segments can be used and consequently less segments have to be considered at retrieval time.

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Video Content Foraging

Cited by 4 publications

References 14 publications

A Multidisciplinary Approach to Unlocking Television Broadcast Archives

A Multidisciplinary Approach to Unlocking Television Broadcast Archives

Assessing user behaviour in news video retrieval

Comparing segmentation strategies for efficient video passage retrieval

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