@inproceedings{823ccf5b9fc545bca9e565c1360d6052,
title = "Rectangular empty parking space detection using sift based classification",
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.",
keywords = "Filtering, Geometric and spatial constraints, Parking space detection, Peak extraction, Radon transform, SIFT, Supervised classification",
author = "Harish Bhaskar and Naoufel Werghi and Saeed Al-Mansoori",
year = "2011",
language = "British English",
isbn = "9789898425478",
series = "VISAPP 2011 - Proceedings of the International Conference on Computer Vision Theory and Application",
pages = "214--220",
booktitle = "VISAPP 2011 - Proceedings of the International Conference on Computer Vision Theory and Application",
note = "International Conference on Computer Vision Theory and Application, VISAPP 2011 ; Conference date: 05-03-2011 Through 07-03-2011",
}