Abstract
After document and image retrieval, shape retrieval is seen as the next step in the search process. Numerous techniques have been proposed to retrieve shapes meta-data considering shapes similarity but these techniques normally suffer from non-interactive running times. A widely used approach, which has its origins in document retrieval, and is successfully been applied for image retrieval, is based on "bag-of-words". Methods using this approach have the potential to support fast, real time retrieval of shapes over the large databases. This research examines these approaches and summarizes the techniques used to convert shapes to their "bag of words" representations. This research also explores the mechanism these techniques adopts to facilitate and enhance interactive search times.