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SGN-5506 Multimedia Analysis and Retrieval, 5 cr |
Alpo Värri, Serkan Kiranyaz, Moncef Gabbouj
Lecture times and places | Target group recommended to | |
Implementation 1 |
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Attendance and completion of 60% Exercises Final Exam
Type | Name | Author | ISBN | URL | Edition, availability, ... | Examination material | Language |
Book | Introduction to MPEG-7 | B. S. Manjunath | 0471 48678 7 | English | |||
Book | Multimedia Information Retrieval and Management | D. Feng et al. | English | ||||
Other literature | Relevant scientific papers and reference book material | English |
Course | O/R |
SGN-2500 Introduction to Pattern Recognition | Obligatory |
SGN-2506 Introduction to Pattern Recognition | Obligatory |
SGN-3010 Digital Image Processing I | Obligatory |
SGN-3016 Digital Image Processing I | Obligatory |
SGN-3106 Digital Video Processing | Obligatory |
SGN-3156 Video Compression | Recommended |
SGN-4200 Digital Audio | Obligatory |
SGN-5016 Multimedia Signal Processing | Recommended |
SGN-5306 Knowledge Mining | Recommended |
Description | Methods of instruction | Implementation | |
Implementation 1 | Course Topic The main topic is the current approaches for searching, browsing, and mining various types of multimedia data such as images, audio and video (audiovisual data). The focus is on applying methods from machine learning and computer vision to these problems. In this course, a broad range of techniques will be studied including multimedia features, video analysis and management, retrieval techniques, spatial indexing methods, long-term learning and Relevance Feedback, audio analysis and retrieval, semantic-based retrieval techniques. Motivation and Scope With the growth of the Internet and developments in imaging technology, very large digital image and video archives have been created and used in numerous applications. Together with the increase in the number of pictorial archives, demands are also growing for methodologies and techniques to store and retrieve audio-visual data. Therefore, understanding and thereby analysis of multimedia content at the semantic level is the only way towards realizing the full potential of emerging digital media technologies aimed at the delivery of compelling multimedia solutions. The integration of knowledge, semantics and low-level multimedia processing for the purpose of automatic semantics extraction from multimedia content is still the subject of active research in academia and industry. |