Multimedia Data Analysis

Teaching Hours and Credit Allocation:   30 Hours, 6 Credits

Course Assessment:  Exam & Coursework

 

Aims

This course examines the analysis of multimedia (e.g. image, video, audio) data in large scale datasets for the purposes of identification and extraction of useful information. Students will be exposed to a large array of techniques, ranging from machine learning and pattern recognition to signal processing and computer vision, for multimedia processing and will gain a deep understanding of the unique challenges that arise in terms of scalability, accuracy and semantics.

 

Learning Outcomes

On completing the course, students will be able to:

  • Use tools for multimedia information analysis.
  • Extract meaningful features from different types of multimedia data.
  • Be able to implement semantic multimedia content classification and annotation.
  • Apply speech and speaker recognition techniques.
  • Know how to perform video indexing and summarization.

 

Content

  • Intelligent tools and techniques for multimedia information analysis.
  • Semantic content analysis and annotation.
  • Feature extraction.
  • Multimedia information processing.
  • Video summarization and indexing.
  • Multimedia databases.
  • Multimedia data applications and future trends.
  • Cross-modal access to information.

 

Reading

  • Data Management for Multimedia Retrieval, K. Selçuk Candan, Maria Luisa Sapino (2010).
  • Semantic Multimedia Analysis and Processing, Evaggelos Spyrou, Dimitris Iakovidis, Phivos Mylonas, 2014, CRC Press.
  • Multimedia Data Mining: A Systematic Introduction to Concepts and Theory, Zhongfei Zhang, Ruofei Zhang, 2008, Chapman and Hall/CRC.