Hierarchical image representation using 3D camera geometry for content-based image retrieval
Abstract
In this paper we present a hierarchical image representation methodology by clustering images with 3D camera geometry in order to efficiently retrieve the images according to user's viewpoint. The framework of our proposed technique is composed of two steps: first the visual correlation analysis between images in a large database is determined by the estimated 3D camera geometry and second images are classified using a constrained agglomerative hierarchical image clustering method to retrieve the images the users search. The constrained agglomerative hierarchical image clustering method provides balanced hierarchical layers, independent of the number of images within the cluster. It also provides a convenient way to browsing, navigating, and categorizing of the images with various viewpoints, illumination, and partial occlusion.
