Content-based Retrieval on Very Large Visual Document Archives

This tutorial will discusses the issues related to content based retrieval in very large dataset of visual documents. Content based retrieval typically is not performed using the visual content itself, rather visual features are extracted and retrieval is performed searching by similarity on the extracted features. Similarity search is a difficult task because efficient techniques to process database or text queries cannot be applied here. Therefore in the last decades researcher have investigated techniques for executing similarity search efficiently and in a scalable way. One popular way to compare similarity between visual documents is the use of global visual features and to measure their similarity (or dissimilarity) by using a similarity (or distance) function. Various indexing strategies and search algorithms based on distance function were defined during the last decade. A relevant research direction has been that of the tree-based access methods, that allow search algorithms just to inspect a small portion of the dataset.