New anchor selection methods for image retrieval

Apostol Natsev; John R. Smith

doi:10.1117/12.479744

10 January 2003 New anchor selection methods for image retrieval

Apostol Natsev, John R. Smith

Proceedings Volume 5021, Storage and Retrieval for Media Databases 2003; (2003) https://doi.org/10.1117/12.479744
Event: Electronic Imaging 2003, 2003, Santa Clara, CA, United States

Abstract

Anchoring is a technique for representing objects by their distances to a few well chosen landmarks, or anchors. Objects are mapped to distance-based feature vectors, which can be used for content-based retrieval, classification, clustering, and relevance feedback of images, audio, and video. The anchoring transformation typically reduces dimensionality and replaces expensive similarity computations in the original domain with simple distance computations in the anchored feature domain, while guaranteeing lack of false dismissals. Anchoring is therefore surprisingly simple, yet effective, and flavors of it have seen application in speech recognition, audio classification, protein homology detection, and shape matching. In this paper, we describe the anchoring technique in some detail and study methods for anchor selection, both from an analytical, as well as empirical, standpoint. Most work to date has largely ignored this problem by fixing the anchors to be the entire set of objects or by using greedy selection from among the set of objects. We generalize previous work by considering anchors from outside of the object space, and by deriving an analytical upper bound on the distance-approximation error of the method.

Citation Download Citation

Apostol Natsev and John R. Smith "New anchor selection methods for image retrieval", Proc. SPIE 5021, Storage and Retrieval for Media Databases 2003, (10 January 2003); https://doi.org/10.1117/12.479744

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available