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Authors: Eric Gabriel 1 ; Ferdinand Hahmann 1 ; Gordon Böer 1 ; Hauke Schramm 2 and Carsten Meyer 2

Affiliations: 1 Kiel University of Applied Sciences, Germany ; 2 Kiel University of Applied Sciences, Faculty of Engineering and Kiel University (CAU), Germany

ISBN: 978-989-758-175-5

Keyword(s): Object Detection, Object Localization, Feature Extraction, Edge Detection, Canny Edge Detection, Structured Edge Detection, Discriminative Generalized Hough Transform.

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

Abstract: Automatic localization of target objects in digital images is an important task in Computer Vision. The Generalized Hough Transform (GHT) and its variant, the Discriminative Generalized Hough Transform (DGHT), are model-based object localization algorithms which determine the most likely object position based on accumulated votes in the so-called Hough space. Many automatic localization algorithms - including the GHT and the DGHT - operate on edge images, using e.g. the Canny or the Sobel Edge Detector. However, if the image contains many edges not belonging to the object of interest (e.g. from other objects, background clutter, noise etc.), these edges cause misleading votes which increase the probability of localization errors. In this paper we investigate the effect of a more sophisticated edge detection algorithm, called Structured Edge Detector, on the performance of a DGHT-based object localization approach. This method utilizes information on the shape of the target object to s ubstantially reduce the amount of non-object edges. Combining this technique with the DGHT leads to a significant localization performance improvement for automatic pedestrian and car detection. (More)

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Paper citation in several formats:
Gabriel, E.; Hahmann, F.; Böer, G.; Schramm, H. and Meyer, C. (2016). Structured Edge Detection for Improved Object Localization using the Discriminative Generalized Hough Transform.In Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4 VISAPP: VISAPP, (VISIGRAPP 2016) ISBN 978-989-758-175-5, pages 393-402. DOI: 10.5220/0005722803930402

@conference{visapp16,
author={Eric Gabriel. and Ferdinand Hahmann. and Gordon Böer. and Hauke Schramm. and Carsten Meyer.},
title={Structured Edge Detection for Improved Object Localization using the Discriminative Generalized Hough Transform},
booktitle={Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4 VISAPP: VISAPP, (VISIGRAPP 2016)},
year={2016},
pages={393-402},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005722803930402},
isbn={978-989-758-175-5},
}

TY - CONF

JO - Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4 VISAPP: VISAPP, (VISIGRAPP 2016)
TI - Structured Edge Detection for Improved Object Localization using the Discriminative Generalized Hough Transform
SN - 978-989-758-175-5
AU - Gabriel, E.
AU - Hahmann, F.
AU - Böer, G.
AU - Schramm, H.
AU - Meyer, C.
PY - 2016
SP - 393
EP - 402
DO - 10.5220/0005722803930402

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