A Configurable Photo Browser Framework for Large Image Collections

Abstract

Image collections are growing at an exponential rate due to the wide availability of inexpensive digital cameras and storage. Current browsers organize photos mostly chronologically, or according to manual tags. For very large collections acquired over several years it can be difficult to locate a particular set of images – even for the owner. Although our visual memory is powerful, it is not always easy to recall all of one’s images. Moreover, it can be very time consuming to find particular images in other peoples image collections. This paper presents a prototype image browser and a plug-in pattern that allows classifiers to be implemented and easily integrated with the image browser such that the user can control the characteristics of the images that are browsed and irrelevant photos are filtered out. The filters can both be content based and based on meta-information. The current version is only employs meta-information which means that large image collections can be indexed efficiently.