ABSTRACT
Understanding huge multimedia collections is a huge challenge. Given a set of hundreds of thousands or millions of images, how to to understand its contents and how to find the images that are relevant for the task at hand? Using a combination of automated methods, visualization, and interaction, known as visual analytics, is probably the only way to go, combining the strengths of man and machine. An overview is given of trends in data visualization and visual analytics is given, and examples of recent work in multimedia analytics are presented. Exploiting meta-data, using interaction with relatively simple visual representations, and alignment with the work flow of users are promising routes, but scalability and evaluation are still challenging.
Index Terms
- Visual Analytics for Multimedia: Challenges and Opportunities
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