NDLI: A Pivot-Based Distributed Pseudo Facial Image Retrieval in Manifold Spaces: An Efficiency Study

Content Provider	IEEE Xplore Digital Library
Author	Yi Zhuang
Copyright Year	2010
Abstract	The research of cognitive science indicates that manifold-learning-based facial image retrieval is based on human perception, which can accurately capture the intrinsic similarity of two facial images. The paper proposes a pivot-based Distributed Pseudo Similarity Retrieval method called DPSR in manifold spaces with the aid of a adjacency distance list (ADL). Specifically, we first construct a two dimensional array, called ADL which records the pair-wise distance between any two facial images with a constraint in the database. Then, the distances are indexed by a B+-tree. Finally, a DPSR process in high-dimensional manifold spaces is transformed into range search over the B+-tree in the single-dimensional space at a filtering level. Extensive experimental studies show that the DPSR outperforms the conventional sequential scan in manifold spaces by a large margin, especially for the large high-dimensional datasets.
Starting Page	508
Ending Page	514
File Size	772640
Page Count	7
File Format	PDF
ISBN	9781424484843
DOI	10.1109/NSS.2010.59
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-09-01
Publisher Place	Australia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Manifolds Filtering Clustering algorithms Artificial neural networks Facial image retrieval High-dimensional indexing Face Indexing
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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