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Author: Avi Bleiweiss

Affiliation: Intel Corporation, United States

ISBN: 978-989-758-018-5

Keyword(s): Dimensionality Reduction, Image Decomposition, Disjoint Set, Histogram of Oriented Gradient.

Related Ontology Subjects/Areas/Topics: Clustering ; Feature Selection and Extraction ; Pattern Recognition ; Similarity and Distance Learning ; Sparsity ; Theory and Methods

Abstract: A common objective in multi class, image analysis is to reduce the dimensionality of input data, and capture the most discriminant features in the projected space. In this work, we investigate a system that first finds clusters of similar points in feature space, using a nearest neighbor, graph based decomposition algorithm. This process transforms the original image data on to a subspace of identical dimensionality, but at a much flatter, color gamut. The intermediate representation of the segmented image, follows an effective, local descriptor operator that yields a marked compact feature vector, compared to the one obtained from a descriptor, immediately succeeding the native image. For evaluation, we study a generalized, multi resolution representation of decomposed images, parameterized by a broad range of a decreasing number of clusters. We conduct experiments on both non and correlated image sets, expressed in raw feature vectors of one million elements each, and demonstrate r obust accuracy in applying our features to a linear SVM classifier. Compared to state-of-the-art systems of identical goals, our method shows increased dimensionality reduction, at a consistent feature matching performance. (More)

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Paper citation in several formats:
Bleiweiss, A. (2014). Dimensionality Reduction of Features using Multi Resolution Representation of Decomposed Images.In Proceedings of the 3rd International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-758-018-5, pages 316-324. DOI: 10.5220/0004917403160324

@conference{icpram14,
author={Avi Bleiweiss.},
title={Dimensionality Reduction of Features using Multi Resolution Representation of Decomposed Images},
booktitle={Proceedings of the 3rd International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2014},
pages={316-324},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004917403160324},
isbn={978-989-758-018-5},
}

TY - CONF

JO - Proceedings of the 3rd International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - Dimensionality Reduction of Features using Multi Resolution Representation of Decomposed Images
SN - 978-989-758-018-5
AU - Bleiweiss, A.
PY - 2014
SP - 316
EP - 324
DO - 10.5220/0004917403160324

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