Michael Christel's Automated metadata in multimedia information systems: PDF

By Michael Christel

ISBN-10: 1598297716

ISBN-13: 9781598297713

ISBN-10: 1598297724

ISBN-13: 9781598297720

Advancements in community bandwidth besides dramatic drops in electronic garage and processing charges have ended in the explosive progress of multimedia (combinations of textual content, picture, audio, and video) assets on the web and in electronic repositories. a collection of laptop applied sciences offering speech, picture, and traditional language realizing can instantly derive descriptive metadata for such assets. problems for finish clients happen, notwithstanding, with the large quantity and ranging caliber of automatic metadata for multimedia info structures. This lecture surveys computerized metadata construction tools for facing multimedia details assets, utilizing broadcast information, documentaries, and oral histories as examples. concepts for making improvements to the application of such metadata are mentioned, together with computationally in depth techniques, leveraging multimodal redundancy, folding in context, and leaving precision-recall tradeoffs below person regulate. Interfaces development from immediately generated metadata are awarded, illustrating using video surrogates in multimedia info structures. conventional info retrieval evaluate is mentioned throughout 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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Extra resources for Automated metadata in multimedia information systems: creation, refinement, use in surrogates, and evaluation

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At that time, the Cranfield tradition of using retrieval experiments on test collections was already well established, but progress in the text information retrieval field was hampered by the lack of easily accessible, realistically large test collections. Large test collections did exist, but they were proprietary, with each collection usually the result of a single company’s efforts. The proprietary nature of the collections also biased them in various ways. TREC was conceived as a way to address this need for large, unbiased test collections.

What if the proper name were misrecognized? How can mistakes in proper name automatic tagging be recognized and subsequently corrected for a broadcast news corpus? A baseball video corpus? A documentary corpus? A general video corpus? • • • • 33 chapter 4 Multimedia Surrogates To illustrate earlier sections, multimedia surrogates of thumbnails and storyboards have been shown in figures. In information retrieval, the term “document surrogate” is used to label information that serves as the representation for the full document, such as a title, abstract, table of contents, set of keywords, or combinations of these descriptors.

Suppose they only include color and no edges or textures, then regardless of how large the training set is, the road detector will perform poorly because of a mismatch between the features and the road concept. The Lucas–Kanade method for optical flow estimation [72] is a computationally expensive but accurate way of assessing camera or object motion by looking at pixel-by-pixel differences between image frames. The method is expensive in that every pair of sequential frames in a video could be compared for highest precision, and every pixel considered in each comparison.

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Automated metadata in multimedia information systems: creation, refinement, use in surrogates, and evaluation by Michael Christel

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