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partial solution to the management problem. It may well be the case that the problem is not so much of finding something in a collection but that the collection itself needs to be investigated.

Here, we look at visual multimedia information management in a ‹queryless› context. The user is faced with a (large) number of multimedia data. The tools should help the user in getting a comprehensive view of the content of these collections effectively. The base system is a simple view system that shows items in a random order. Whereas this may look as a purely technical challenge, its development involves the comprehension of human perception of visual content and leads to problems that do not just find analytical solutions.

From the context in which these tools should be developed, we look at what tools we have at hand for achieving our goal and assemble them in a unified context. This directs us towards the concept of «Collection Guiding» [CGUIDE] where the user embarks for a visit through the multimedia space automatically created using state-of-the-art techniques for automated visual document analysis. Our approach


re-locates the user at the center of the system and sets back the emphasis on Human-Computer Interaction.

Human perception of visual multimedia documents

Studies show that a person may handle simultaneously less than a thousand photos (clearly, this depends on the diversity and task). Nowadays photo cameras may store some hundreds of photos. The well-known GIMP-Savvy free photo archive contains about 27,000 images and Google indexes 425 million images acquired from the WWW (as of February 2004). A commercial image provider like Corbis should manage a catalog of more than a million items to be competitive.

In the latter case, it is important that no ‹dark zone› is created. In other words, the manager should keep a fluent access to any item within the database. Hence, the problem is twofold. The manager should first know that an image of a given type exists and then know how to formulate a demand to the system to actually retrieve it.

While Content-based Visual Indexing tools that we discuss in the next paragraph may solve the second

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