Welcome to the InfoSci Platform
Multimodal Analysis in Multimedia Using Symbolic Kernels

Multimodal Analysis in Multimedia Using Symbolic Kernels

Hrishikesh B. Aradhye, Chitra Dorai
Copyright: © 2005 |Pages: 6
ISBN13: 9781591405573|ISBN10: 1591405572|EISBN13: 9781591405597
DOI: 10.4018/978-1-59140-557-3.ch160
Cite Chapter Cite Chapter

MLA

Aradhye, Hrishikesh B., and Chitra Dorai. "Multimodal Analysis in Multimedia Using Symbolic Kernels." Encyclopedia of Data Warehousing and Mining, edited by John Wang, IGI Global, 2005, pp. 842-847. https://doi.org/10.4018/978-1-59140-557-3.ch160

APA

Aradhye, H. B. & Dorai, C. (2005). Multimodal Analysis in Multimedia Using Symbolic Kernels. In J. Wang (Ed.), Encyclopedia of Data Warehousing and Mining (pp. 842-847). IGI Global. https://doi.org/10.4018/978-1-59140-557-3.ch160

Chicago

Aradhye, Hrishikesh B., and Chitra Dorai. "Multimodal Analysis in Multimedia Using Symbolic Kernels." In Encyclopedia of Data Warehousing and Mining, edited by John Wang, 842-847. Hershey, PA: IGI Global, 2005. https://doi.org/10.4018/978-1-59140-557-3.ch160

Export Reference

Mendeley
Favorite

Abstract

The rapid adoption of broadband communications technology, coupled with ever-increasing capacity-to-price ratios for data storage, has made multimedia information increasingly more pervasive and accessible for consumers. As a result, the sheer volume of multimedia data available has exploded on the Internet in the past decade in the form of Web casts, broadcast programs, and streaming audio and video. However, indexing, search, and retrieval of this multimedia data is still dependent on manual, text-based tagging (e.g., in the form of a file name of a video clip). However, manual tagging of media content is often bedeviled by an inadequate choice of keywords, incomplete and inconsistent terms used, and the subjective biases of the annotator introduced in his or her descriptions of content adversely affecting accuracy in the search and retrieval phase. Moreover, manual annotation is extremely time-consuming, expensive, and unscalable in the face of ever-growing digital video collections. Therefore, as multimedia get richer in content, become more complex in format and resolution, and grow in volume, the urgency of developing automated content analysis tools for indexing and retrieval of multimedia becomes easily apparent.

Request Access

You do not own this content. Please login to recommend this title to your institution's librarian or purchase it from the IGI Global bookstore.