Multimedia Search and Retrieval

This class is usually taught by Markus Schedl in the winter term. The class is taught in English.

Information for the current semester (if available):

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Class Objectives and Content

Students will learn the basics in multimedia processing and analysis (feature extraction, feature analysis, pattern discovery, data analysis), which are required to understand and build multimedia search and retrieval systems. We will first cover the four most important types of multimedia data (text, audio/music, image, video) individually, focusing on particularities of each data source and on aspects of feature extraction and data cleaning. After the first set of lectures, students will have acquired a solid knowledge in state-of-the-art feature extraction techniques. Hereafter, methods to analyze the extracted features will be discussed, in particular, methods of data analysis for pattern discovery and visualization. This will be complemented by a practical project in which students will apply the techniques learned.


The main topics covered include: 

  • Search and retrieval in multimedia repositories
  • Text features
  • Audio and music features
  • Image features
  • Video features
  • Data fusion of multimodal data
  • Interfaces and browsing
  • Linear and non-linear models for data analysis

 

Practical Exercise

The practical task will deal with retrieval of diverse images for given locations (details to follow). The practical exercise is mandatory and will contribute 50% to the final grade.