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Authors: Boguslaw Cyganek 1 and Katarzyna Socha 2

Affiliations: 1 AGH University of Science and Technology, Poland ; 2 Polish Academy of Sciences, Poland

Keyword(s): Object Recognition, Tensor Processing, Higher-Order Singular Value Decomposition, Parallel Algorithms.

Abstract: In this paper a novel parallel algorithm for the tensor based classifiers for object recognition in digital images is presented. Classification is performed with an ensemble of base classifiers, each operating in the orthogonal subspaces obtained with the Higher-Order Singular Value Decomposition (HOSVD) of the prototype pattern tensors. Parallelism of the system is realized through the functional and data decompositions on different levels of computations. First, the parallel implementation of the HOSVD is presented. Then, the second level of parallelism is gained by partitioning the input dataset. Each of the partitions is used to train a separate tensor classifiers of the ensemble. Despite the computational speed-up and lower memory requirements, also accuracy of the ensemble showed to be higher compared to a single classifier. The method was tested in the context of object recognition in computer vision. The experiments show high accuracy and accelerated performance both in the t raining and classification stages. (More)

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Paper citation in several formats:
Cyganek, B. and Socha, K. (2014). Novel Parallel Algorithm for Object Recognition with the Ensemble of Classifiers based on the Higher-Order Singular Value Decomposition of Prototype Pattern Tensors. In Proceedings of the 9th International Conference on Computer Vision Theory and Applications (VISIGRAPP 2014) - Volume 1: VISAPP; ISBN 978-989-758-004-8; ISSN 2184-4321, SciTePress, pages 648-653. DOI: 10.5220/0004745606480653

@conference{visapp14,
author={Boguslaw Cyganek. and Katarzyna Socha.},
title={Novel Parallel Algorithm for Object Recognition with the Ensemble of Classifiers based on the Higher-Order Singular Value Decomposition of Prototype Pattern Tensors},
booktitle={Proceedings of the 9th International Conference on Computer Vision Theory and Applications (VISIGRAPP 2014) - Volume 1: VISAPP},
year={2014},
pages={648-653},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004745606480653},
isbn={978-989-758-004-8},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 9th International Conference on Computer Vision Theory and Applications (VISIGRAPP 2014) - Volume 1: VISAPP
TI - Novel Parallel Algorithm for Object Recognition with the Ensemble of Classifiers based on the Higher-Order Singular Value Decomposition of Prototype Pattern Tensors
SN - 978-989-758-004-8
IS - 2184-4321
AU - Cyganek, B.
AU - Socha, K.
PY - 2014
SP - 648
EP - 653
DO - 10.5220/0004745606480653
PB - SciTePress

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