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Output details

13 - Electrical and Electronic Engineering, Metallurgy and Materials

Queen Mary University of London : A - Electrical and Electronic engineering

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Output 25 of 60 in the submission

Article title

Fast Multidimensional Entropy Estimation by k-d Partitioning

Type

D - Journal article

DOI

10.1109/LSP.2009.2017346

Title of journal

IEEE Signal Processing Letters

Article number

Volume number

Issue number

First page of article

537

ISSN of journal

1070-9908

Year of publication

2009

URL

http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=4897236

Number of additional authors

Additional information

Entropy estimation for multidimensional distributions suffers from the 'curse of dimensionality' beyond only a few (about 5) dimensions. This paper introduces a new fast method, scaling as O(n log(n)), several orders of magnitude faster than competing methods, allowing 30 or more dimensions. Method applied to build a new image feature extractor, multi-dimensional Scale Saliency (MDSS), which 'remarkably decreases computation time' compared to previous techniques [Suau & Escolano, http://bit.ly/1eZl5Bf]. This has proved to be practical and computationally efficient, and has been applied to shape comparison [http://bit.ly/HlTTRH], active robot vision [http://bit.ly/16DXk1k], and texture categorization [http://bit.ly/16DXkyw].

Interdisciplinary

Cross-referral requested

Research group

None

Proposed double-weighted

Double-weighted statement

Reserve for a double-weighted output

Non-English

English abstract