Approaches to consumer image organization based on semantic categories

The primary goal of the current research was to develop image categorization algorithms that are more consistent with users' search strategies for their personal image collections. Other goals were to provide users with the option of correcting and labeling these image groups and to understand user behaviors and needs while they are using an automated image-organization system. The main focus of this paper is to provide automatic organization of images by two of the most important semantic classes in the consumer domain-events and people. Methods are described for automatically producing meaningful groups of images whereby each group depicts an event as well as clusters of similar faces in users' collections. Given that the proposed system envisions user interaction and is intended for organizing and searching personal collections, a usability study focused on consumers was conducted to gauge the performance of the system.