Paper Info
Title
Hierarchical Online Image Representation Based On 3d Camera Geometry
Abstract
Within this paper, we present a hierarchical online image representation method with 3D camera position to efficiently summarize and classify the images on the web. The framework of our proposed hierarchical online image representation methodology is composed of multiple layers: at the lowest layer in the hierarchical structure, relationship between multiple images is represented by their recovered 3D camera parameters by automatic feature detection and matching. At the upper layers, images are classified using constrained agglomerative hierarchical image clustering techniques, in which the feature space established at the lowest layer consists of the camera's 3D position. Constrained agglomerative hierarchical online image clustering method is efficient to balance the hierarchical layers whether images in the cluster are many or not. Our proposed hierarchical online image representation method can be used to classify online images within large image repositories by their camera view position and orientation. It provides a convenient way to image browsing, navigating and categorizing of the online images that have various view points, illumination, and partial occlusion.
Year
Venue
Keywords
2009
VISAPP 2009: PROCEEDINGS OF THE FOURTH INTERNATIONAL CONFERENCE ON COMPUTER VISION THEORY AND APPLICATIONS, VOL 2
Hierarchical image clustering
Field
DocType
Citations 
Hierarchical clustering,Computer vision,Feature vector,Pattern recognition,Feature detection,Feature detection (computer vision),3d camera,Computer science,Image representation,Pyramid (image processing),Artificial intelligence,Cluster analysis
Conference
2
PageRank 
References 
Authors
0.37
1
2
Name
Order
Citations
PageRank
Sang Min Yoon112919.66
Holger Graf25615.10