Automated metadata in multimedia information systems: by Michael Christel

By Michael Christel

Advancements in community bandwidth in addition to dramatic drops in electronic garage and processing charges have ended in the explosive development of multimedia (combinations of textual content, photograph, audio, and video) assets on the net and in electronic repositories. a collection of desktop applied sciences offering speech, photograph, and common language realizing can immediately derive descriptive metadata for such assets. problems for finish clients take place, although, with the super quantity and ranging caliber of automatic metadata for multimedia info platforms. This lecture surveys computerized metadata production tools for facing multimedia info assets, utilizing broadcast information, documentaries, and oral histories as examples. options for bettering the software of such metadata are mentioned, together with computationally extensive methods, leveraging multimodal redundancy, folding in context, and leaving precision-recall tradeoffs below person keep an eye on. Interfaces development from immediately generated metadata are awarded, illustrating using video surrogates in multimedia details platforms. conventional info retrieval overview is mentioned during the annual nationwide Institute of criteria and know-how TRECVID discussion board, with experiments on exploratory seek extending the dialogue past fact-finding to broader, long run seek actions of studying, research, synthesis, and discovery.

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Success is measured based on quantities of relevant documents retrieved, in particular, the metrics of recall and precision. The two are combined into a single measure of performance, average precision, which measures precision after each relevant document is retrieved for a given topic. Average precision is then itself averaged 48 automated metadata in multimedia information systems over all of the topics to produce a mean average precision (MAP) metric for evaluating a system’s performance. For TRECVID video searches, the individual “documents” retrieved are shots, where a shot is defined as a single continuous camera operation without an editor’s cut, fade, or dissolve—typically 2–10 seconds long for broadcast news.

82] and including the following: intriguing the user to watch the whole video (movie trailers), quickly deciding if the program is worth watching (electronic program guide), locating specific regions of interest (lecture overview), collapsing highly redundant footage into the subset with important information (surveillance executive summary). For most applications, multimedia summaries mainly serve two functions, again drawing from [82]: an indicative function, where the summary is used to indicate what topics of information are contained in the original multimedia document; and the informative function, where the summaries are used to cover the information in the source as much as possible, subject to the summary length.

6: Collection-level metadata of common text phrases for 414 HistoryMakers story segments returned from “baseball” query (left), and the common text for the 20 baseball segments discussing Kansas City (right). 7: Example of VOCR process producing incorrect output “COUNA” that could be cleaned up through statistical processing for “Los Angeles Sheriff ” candidates. For news, this could mean mining only news web sites rather than the Web in general, mining the same period as the VOCR’d broadcast in question leveraging from administrative metadata, or mining just that particular broadcaster’s web site.

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Automated metadata in multimedia information systems: by Michael Christel
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