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Authors: Zhu Teng 1 ; Baopeng Zhang 1 ; Onecue Kim 2 and Dong-Joong Kang 3

Affiliations: 1 Beijing Jiaotong University, China ; 2 Pusan National university, Korea, Republic of ; 3 Pusan National University, Korea, Republic of

Keyword(s): Regional SVM, Object Detection, Spatial Model.

Abstract: This paper presents regional Support Vector Machine (SVM) classifiers with a spatial model for object detection. The conventional SVM maps all the features of training examples into a feature space, treats these features individually, and ignores the spatial relationship of the features. The regional SVMs with a spatial model we propose in this paper take into account a 3-dimentional relationship of features. One-dimensional relationship is incorporated into the regional SVMs. The other two-dimensional relationship is the pairwise relationship of regional SVM classifiers acting on features, and is modelled by a simple conditional random field (CRF). The object detection system based on the regional SVM classifiers with the spatial model is demonstrated on several public datasets, and the performance is compared with that of other object detection algorithms.

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Paper citation in several formats:
Teng, Z.; Zhang, B.; Kim, O. and Kang, D. (2014). Regional SVM Classifiers with a Spatial Model for Object Detection. 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 372-379. DOI: 10.5220/0004679003720379

@conference{visapp14,
author={Zhu Teng. and Baopeng Zhang. and Onecue Kim. and Dong{-}Joong Kang.},
title={Regional SVM Classifiers with a Spatial Model for Object Detection},
booktitle={Proceedings of the 9th International Conference on Computer Vision Theory and Applications (VISIGRAPP 2014) - Volume 1: VISAPP},
year={2014},
pages={372-379},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004679003720379},
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 - Regional SVM Classifiers with a Spatial Model for Object Detection
SN - 978-989-758-004-8
IS - 2184-4321
AU - Teng, Z.
AU - Zhang, B.
AU - Kim, O.
AU - Kang, D.
PY - 2014
SP - 372
EP - 379
DO - 10.5220/0004679003720379
PB - SciTePress