Navigating News Programs in Large TV-Streams: A Knowledge-Based Approach

Navigating News Programs in Large TV-Streams: A Knowledge-Based Approach

Walid Mahdi (College of Computers and Information Technology, Taif University, Taif, Saudi Arabia) and Tarek Zlitni (Higher Institute of Computer Science and Multimedia, University of Sfax, Sfax, Tunisia)
Copyright: © 2016 |Pages: 19
DOI: 10.4018/IJKSR.2016010106
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The different uses of large TV streams have continued to diversify since the appearance of digital TV. For conveniently retrieving and navigating in TV streams, users are often interested in new content-based multimedia applications of high added value such as Interactive TV, Video on Demand (VoD), YouTube or Dailymotion. These applications offer fast and easy access to best explore a particular TV program. So, the automatic process of TV program identification and their internal segmentation facilitate the availability of these programs. Therefore, it is necessary at first, to be able to retrieve a particular program within a large TV stream and secondly segment this program into semantic units related to appropriate retrieval entities. In this paper, the major originality of the authors' approach is the use of contextual and operational characteristics of TV production/post-production rules as prior knowledge that captures the structure for recurrent TV news program content. The authors validate their approach by experiments conducted using the TRECVID dataset that demonstrate its robustness.
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Intensive research efforts were directed to content-based video indexing (Hu et al. 2011; Choroś, 2015b). The video documents are habitually incorporated in large TV streams. Therefore, efficient indexing of TV programs requires firstly their localization and extraction them from the stream. A class of works focuses on locating programs in TV stream, where as other kind of works is interested on the internal structuring of TV programs. Few efficient contributions have been proposed to structure TV streams. For example, to identify the various programs in TV stream, Naturel and Gros (2008) created hash-table containing key-frame signatures of program references. Then, he used signature similarity between the stream signal and the hash-table elements to locate the programs. The method presented by Manson (2009) aims to detect automatically programs in TV streams. The purpose of its work is to detect the limits of broadcasted programs. The method first detects inter-programs as repeated sequences in the TV stream in order to deduce the programs boundaries. The major drawback of these contributions is that they focus only on programs localization in TV streams without reaching the second level: the internal structuring where we can extract the semantics.

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