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Querying Multimedia Content with Automated Systems: Results and Overview

This document presents a comprehensive overview of an automated multimedia content querying system that analyzes and structures various media types, including text and video. It outlines the objectives, methodology, and experimental results achieved. The system illustrates the effectiveness of advanced query processing techniques and offers insights into the architecture. Additionally, it highlights key references for further reading on related multimedia processing methods. The findings emphasize the potential for improvements in media handling and structure, paving the way for future research in the field.

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Querying Multimedia Content with Automated Systems: Results and Overview

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  1. TITLE NAME MAJOR CONTACT MAIL ex( bjlee@bi.snu.ac.kr) RESULT backgrounds A a • A • A • A • A • A • A • Aa • 실험 결과 : Objectives A a 그림1. SYSTEM OVERVIEW RESULT GRAPH RESULT CHART 시스템 구조 • a • A • A • A • A • A Summary • A • A • A • A • A Experiment • A • A • A • A • A • . References • Myron Flickner, HarpreetSawhney, Wayne Niblack, Jonathan Ashley, Qian Huang, Byron Dom, Monika Gorkani, Jim Hafner, Denis Lee, DragutinPetkovic, David Steele, and Peter Yanker, “Query by image and video content: The QBIC system”, “Computer”, Volume 28 Issue 9, September 1995 • Kenichi Minami, Akihito Akutsu, Hiroshi Hamada, and YoshinobuTonomura, “Video Handling with Music and Speech Detection”, “Multimedia”, Volume 5 Issue 3, July 1998 • HuipingLi, David Doermann, and Omid Kia, “Automatic text detection and tracking in digital video”, “Institute of Electrical and Electronics Engineers”, “Image Processing”, Volume 9 Issue 1, January 2000 • J.-P. Poli, "An Automatic Television Stream Structuring System for Television Archives Holders", Multimedia Systems, Volume 14, Number 5, September 2008 • G. Manson and S.-A. Berranim "Automatic TV Broadcast Structuring", International Journal of Digital Multimedia Broadcasting, vol. 2010, Article ID 153160, January 2010 • Jae Woo Ko, Woo Jin Song, “Analysis-by-synthesis HomomorphicVocoder Using Mel-cepstrum”, “대한 전자공학회”, 7권, 1호, 1994 • Andrew Y. Ng, Michael I. Jordan, On Discriminative vs. Generative classifiers: A comparison of logistic regression and naïve Bayes, Advances in neural information processing systems, Vol.2, No. 14, pp. 841-848, 2002 표1. 결과 Seoul National University, Seoul 151-744, Korea

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