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Authors: Michael Gschwandtner ; Andreas Uhl and Andreas Unterweger

Affiliation: University of Salzburg, Austria

Keyword(s): Integral Image, Resizing, Object Detection, Performance.

Related Ontology Subjects/Areas/Topics: Computer Vision, Visualization and Computer Graphics ; Image Formation and Preprocessing ; Image Generation Pipeline: Algorithms and Techniques

Abstract: In this paper, we present an approach to resize integral images directly in the integral image domain. For the special case of resizing by a power of two, we propose a highly parallelizable variant of our approach, which is identical to bilinear resizing in the image domain in terms of results, but requires fewer operations per pixel. Furthermore, we modify a parallelized state-of-the-art object detection algorithm which makes use of integral images on multiple scales so that it uses our approach and compare it to the unmodified implementation. We demonstrate that our modification allows for an average speedup of 6.38% on a dual-core processor with hyper-threading and 12.6% on a 64-core multi-processor system, respectively, without impacting the overall detection performance. Moreover, we show that these results can be extended to a whole class of object detection algorithms.

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Paper citation in several formats:
Gschwandtner, M.; Uhl, A. and Unterweger, A. (2014). Speeding Up Object Detection - Fast Resizing in the Integral Image Domain. In Proceedings of the 9th International Conference on Computer Vision Theory and Applications (VISIGRAPP 2014) - Volume 2: VISAPP; ISBN 978-989-758-003-1; ISSN 2184-4321, SciTePress, pages 64-72. DOI: 10.5220/0004678000640072

@conference{visapp14,
author={Michael Gschwandtner. and Andreas Uhl. and Andreas Unterweger.},
title={Speeding Up Object Detection - Fast Resizing in the Integral Image Domain},
booktitle={Proceedings of the 9th International Conference on Computer Vision Theory and Applications (VISIGRAPP 2014) - Volume 2: VISAPP},
year={2014},
pages={64-72},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004678000640072},
isbn={978-989-758-003-1},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 9th International Conference on Computer Vision Theory and Applications (VISIGRAPP 2014) - Volume 2: VISAPP
TI - Speeding Up Object Detection - Fast Resizing in the Integral Image Domain
SN - 978-989-758-003-1
IS - 2184-4321
AU - Gschwandtner, M.
AU - Uhl, A.
AU - Unterweger, A.
PY - 2014
SP - 64
EP - 72
DO - 10.5220/0004678000640072
PB - SciTePress