Energy based Descriptors and their Application for Car Detection

Radovan Fusek, Eduard Sojka, Karel Mozdřeň, Milan Šurkala

2014

Abstract

In this paper, we propose a novel technique for object description. The proposed method is based on investigation of energy distribution (in the image) that describes the properties of objects. The energy distribution is encoded into a vector of features and the vector is then used as an input for the SVM classifier. Generally, the technique can be used for detecting arbitrary objects. In this paper, however, we demonstrate the robustness of the proposed descriptors for solving the problem of car detection. Compared with the state-of-the-art descriptors (e.g. HOG, Haar-like features), the proposed approach achieved better results, especially from the viewpoint of dimensionality of the feature vector; the proposed approach is able to successfully describe the objects of interest with a relatively small set of numbers without the use of methods for the reduction of feature vector.

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Paper Citation


in Harvard Style

Fusek R., Sojka E., Mozdřeň K. and Šurkala M. (2014). Energy based Descriptors and their Application for Car Detection . In Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2014) ISBN 978-989-758-003-1, pages 492-499. DOI: 10.5220/0004685804920499


in Bibtex Style

@conference{visapp14,
author={Radovan Fusek and Eduard Sojka and Karel Mozdřeň and Milan Šurkala},
title={Energy based Descriptors and their Application for Car Detection},
booktitle={Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2014)},
year={2014},
pages={492-499},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004685804920499},
isbn={978-989-758-003-1},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2014)
TI - Energy based Descriptors and their Application for Car Detection
SN - 978-989-758-003-1
AU - Fusek R.
AU - Sojka E.
AU - Mozdřeň K.
AU - Šurkala M.
PY - 2014
SP - 492
EP - 499
DO - 10.5220/0004685804920499