Finding similar images quicky using object shapes

Shen, Heng Tao (2001). Finding similar images quicky using object shapes. In: Henrique Paques, Ling Liu and David Grossman, Proceedings of the 2001 ACM CIKM : Tenth International Conference on Information and Knowledge Management. The 10th International Conference on Information and knowledge management, Atlanta, Georgia, USA, (498-506). 05-10 November 2000. doi:10.1145/502585.502669


Author Shen, Heng Tao
Title of paper Finding similar images quicky using object shapes
Conference name The 10th International Conference on Information and knowledge management
Conference location Atlanta, Georgia, USA
Conference dates 05-10 November 2000
Proceedings title Proceedings of the 2001 ACM CIKM : Tenth International Conference on Information and Knowledge Management
Place of Publication New York , U. S. A.
Publisher ACM
Publication Year 2001
Sub-type Fully published paper
DOI 10.1145/502585.502669
ISBN 1581134363
9781581134360
Editor Henrique Paques
Ling Liu
David Grossman
Start page 498
End page 506
Total pages 9
Language eng
Formatted Abstract/Summary
Retrieving images from a large image collection has been an active area of research. Most of the existing works have focused on content representation. In this paper, we address the issue of identifying relevant images quickly. This is important in order to meet the users' performance requirements. We propose a framework for fast image retrieval based on object shapes extracted from objects within images. The framework builds a hierarchy of approximations on object shapes such that shape representation at a higher level is a coarser representation of a shape at the lower level. In other words, multiple shapes at a lower level can be mapped into a single shape at a higher level. In this way, the hierarchy serves to partition the database at various granularities. Given a query shape, by searching only the relevant paths in the hierarchy, a large portion of the database can thus be pruned away. We propose the angle mapping (AM) method to transform a shape from one level to another (higher) level. AM essentially replaces some edges of a shape by a smaller number of edges based on the angles between the edges, thus reducing the complexity of the original shape. Based on the framework, we also propose two hierarchical structures to facilitate speedy retrieval. The first, called Hierarchical Partitioning on Shape Representation (HPSR), uses the shape representation as the indexing key. The second, called Hierarchical Partitioning on Angle Vector (HPAV), captures the angle information from the shape representation. We conducted an extensive study on both methods to see their quality and efficiency. Our experiments on sets of images, each of which has objects around from 1 to 30, showed that the framework can provide speedy image retrieval without sacrificing on the quality. Both proposed schemes can improve the efficiency by as much as hundreds of times to sequential scanning. The improvement grows as image database size, objects per image or object dimension increase.
Keyword Partitioning
Shape indexing
Shape representation
Shape-based image retrieval
Q-Index Code E1
Q-Index Status Provisional Code
Institutional Status Unknown
Additional Notes Other Titles: Proceedings of the Tenth International Conference on Conference on Information and Knowledge Management, 2001., Tenth International Conference on Information and Knowledge Management, 10th International Conference on Information and Knowledge Management, CIKM '01

 
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Created: Tue, 16 Nov 2010, 15:36:13 EST by Dr Heng Tao Shen on behalf of School of Information Technol and Elec Engineering