Multi-facet exploration of image collections with an adaptive multi-focus zoomable interface

Sometimes it is not possible for a user to state a retrieval goal explicitly a priori. One common way to support such exploratory retrieval scenarios is to give an overview using a neighborhood-preserving projection of the collection onto two dimensions. However, neighborhood cannot always be preserved in the projection because of the dimensionality reduction. Further, there is usually more than one way to look at a collection of images - and diversity grows with the number of features that can be extracted. We describe an adaptive zoomable interface for exploration that addresses both problems: It makes use of a complex non-linear multi-focal zoom lens that exploits the distorted neighborhood relations introduced by the projection. We further introduce the concept of facet distances representing different aspects of image similarity. Given user-specific weightings of these aspects, the system can adapt to the user´s way of exploring the collection by manipulation of the neighborhoods as well as the projection.