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Authors: Bo Cheng ; Li Zhuo ; Pei Zhang and Jing Zhang

Affiliation: Beijing University of Technology, China

Keyword(s): Vocabulary Tree, Large-scale Image Retrieval, Optimized SIFT, Local Fisher Discriminant Analysis.

Related Ontology Subjects/Areas/Topics: Computer Vision, Visualization and Computer Graphics ; Features Extraction ; Image and Video Analysis

Abstract: In this paper, vocabulary tree based large-scale image retrieval scheme is proposed that can achieve higher accuracy and speed. The novelty of this paper can be summarized as follows. First, because traditional Scale Invariant Feature Transform (SIFT) descriptors are excessively concentrated in some areas of images, the extraction process of SIFT features is optimized to reduce the number. Then, combined with optimized-SIFT, color histogram in Hue, Saturation, Value (HSV) color space is extracted to be another image feature. Moreover, Local Fisher Discriminant Analysis (LFDA) is applied to reduce the dimension of SIFT and color features, which will help to shorten feature-clustering time. Finally, dimension-reduced features are used to generate vocabulary trees which will be used for large-scale image retrieval. The experimental results on several image datasets show that, the proposed method can achieve satisfying retrieval precision.

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Paper citation in several formats:
Cheng, B.; Zhuo, L.; Zhang, P. and Zhang, J. (2014). Large-scale Image Retrieval based on the Vocabulary Tree. 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 299-304. DOI: 10.5220/0004661802990304

@conference{visapp14,
author={Bo Cheng. and Li Zhuo. and Pei Zhang. and Jing Zhang.},
title={Large-scale Image Retrieval based on the Vocabulary Tree},
booktitle={Proceedings of the 9th International Conference on Computer Vision Theory and Applications (VISIGRAPP 2014) - Volume 1: VISAPP},
year={2014},
pages={299-304},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004661802990304},
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 - Large-scale Image Retrieval based on the Vocabulary Tree
SN - 978-989-758-004-8
IS - 2184-4321
AU - Cheng, B.
AU - Zhuo, L.
AU - Zhang, P.
AU - Zhang, J.
PY - 2014
SP - 299
EP - 304
DO - 10.5220/0004661802990304
PB - SciTePress