RECTANGULAR EMPTY PARKING SPACE DETECTION USING SIFT BASED CLASSIFICATION

Harish Bhaskar, Naoufel Werghi, Saeed Al-Mansoori

2011

Abstract

In this paper, we describe a method of combining rectangle detection and scale invariant feature transform (SIFT) analysis for empty parking space detection. A parking space in a parking lot is represented as a rectangular region of pixels in an image captured from an aerial camera. Detecting rectangular parking spaces in a new image involves an alternating scheme of extracting peaks from the Radon transform for the whole image and filtering them against specific geometric and spatial constraints. We then compute SIFT descriptors from these detected rectangular parking spaces and further apply supervised classification methods for detecting empty parking spaces. We demonstrate the performance of our model on several synthetic and real data.

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Paper Citation


in Harvard Style

Bhaskar H., Werghi N. and Al-Mansoori S. (2011). RECTANGULAR EMPTY PARKING SPACE DETECTION USING SIFT BASED CLASSIFICATION . In Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2011) ISBN 978-989-8425-47-8, pages 214-220. DOI: 10.5220/0003358702140220

in Bibtex Style

@conference{visapp11,
author={Harish Bhaskar and Naoufel Werghi and Saeed Al-Mansoori},
title={RECTANGULAR EMPTY PARKING SPACE DETECTION USING SIFT BASED CLASSIFICATION},
booktitle={Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2011)},
year={2011},
pages={214-220},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003358702140220},
isbn={978-989-8425-47-8},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2011)
TI - RECTANGULAR EMPTY PARKING SPACE DETECTION USING SIFT BASED CLASSIFICATION
SN - 978-989-8425-47-8
AU - Bhaskar H.
AU - Werghi N.
AU - Al-Mansoori S.
PY - 2011
SP - 214
EP - 220
DO - 10.5220/0003358702140220