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Authors: Christopher Bulla and Andreas Weissenburger

Affiliation: RWTH Aachen University, Germany

Keyword(s): Object Detection, Local Features, SIFT.

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

Abstract: In this paper, we present a descriptor architecture, SIFText, that combines texture, shape and color information in one descriptor. The respective descriptor parts are weighted according to the underlying image content, thus we are able to detect and locate low-textured objects in images without performance losses for textured objects. We furthermore present a matching strategy beside the frequently used nearest neighbor matching that has been especially designed for the proposed descriptor. Experiments on synthetically generated images show the improvement of our descriptor in comparison to the standard SIFT descriptor. We show that we are able to detect more features in non-textured regions, which facilitates an accurate detection of non-textured objects. We further show that the performance of our descriptor is comparable to the performance of the SIFT descriptor for textured objects.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Bulla, C. and Weissenburger, A. (2015). Detection of Low-textured Objects. In Proceedings of the 10th International Conference on Computer Vision Theory and Applications (VISIGRAPP 2015) - Volume 3: VISAPP; ISBN 978-989-758-090-1; ISSN 2184-4321, SciTePress, pages 265-273. DOI: 10.5220/0005269602650273

@conference{visapp15,
author={Christopher Bulla and Andreas Weissenburger},
title={Detection of Low-textured Objects},
booktitle={Proceedings of the 10th International Conference on Computer Vision Theory and Applications (VISIGRAPP 2015) - Volume 3: VISAPP},
year={2015},
pages={265-273},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005269602650273},
isbn={978-989-758-090-1},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 10th International Conference on Computer Vision Theory and Applications (VISIGRAPP 2015) - Volume 3: VISAPP
TI - Detection of Low-textured Objects
SN - 978-989-758-090-1
IS - 2184-4321
AU - Bulla, C.
AU - Weissenburger, A.
PY - 2015
SP - 265
EP - 273
DO - 10.5220/0005269602650273
PB - SciTePress

- Science and Technology Publications, Lda.
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