Title
Google image swirl, a large-scale content-based image browsing system
Abstract
We demonstrate the first large-scale image browsing system applied to 200,000 popular queries which utilizes image content to organize image search results. Given a query, the system extracts image content features such as color, shape, local features, face signatures and metadata from up to 1000 image results, and hierarchically clusters them to form an exemplar tree. A dynamic web-based user interface allows the user to navigate this hierarchy, allowing fast and interactive browsing. The exemplars of each cluster provide a comprehensive visual overview of the query results, and allow the user to quickly navigate to the images of interest.
Year
DOI
Venue
2010
10.1109/ICME.2010.5583195
ICME
Keywords
Field
DocType
image shape,pattern clustering,image content,local features,google image swirl,interactive browsing,online front-ends,image browsing,dynamic web-based user interface,image content feature extraction,large-scale content-based image browsing system,image organization,exemplar tree,exemplar images,feature extraction,image color,metadata,query processing,face signatures,face,navigation,user interfaces,hierarchical clustering,image features,space technology,layout
Metadata,Computer vision,Automatic image annotation,Space technology,Computer science,Image retrieval,Feature extraction,Artificial intelligence,Hierarchy,User interface,Dynamic web page
Conference
ISSN
ISBN
Citations 
1945-7871
978-1-4244-7491-2
6
PageRank 
References 
Authors
0.53
2
6
Name
Order
Citations
PageRank
Yushi Jing161628.14
Henry A. Rowley22724479.65
Charles R. Rosenberg360.53
Jingbin Wang447220.56
Ming Zhao51105.99
Michele Covell670678.42