Easy Categorisation of Large Image Collections by Automatic Analysis and Information Visualization
Marcel Worring · UvA-DARE (University of Amsterdam) · 2013
A large part of our history as well as our daily lives is captured in visual data. Understanding visual collections requires careful categorization to reveal expected as well as hidden relations. Performing this categorization manually is a demanding and cumbersome process. On the other hand automatic methods still have limitations in performance. An optimal approach brings together the power of automatic bulk categorization with detailed and careful expert annotation. In this paper we show how advanced visualizations can aid the categorization and subsequent exploration processes.