Authors:
Troels H. P. Jensen
;
Helge T. Schmidt
;
Niels D. Bodin
;
Kamal Nasrollahi
and
Thomas B. Moeslund
Affiliation:
Aalborg University, Denmark
Keyword(s):
Computer Vision, Parking, Convolutional Neural Network, Deep Neural Network, Deep Learning.
Related
Ontology
Subjects/Areas/Topics:
Computer Vision, Visualization and Computer Graphics
;
Features Extraction
;
Image and Video Analysis
Abstract:
With the number of privately owned cars increasing, the issue of locating an available parking space becomes
apparant. This paper deals with the problem of verifying if a parking space is vacant, using a vision based
system overlooking parking areas. In particular the paper proposes a binary classifier system, based on a Con-
volutional Neural Network, that is capable of determining if a parking space is occupied or not. A benchmark
database consisting of images captured from different parking areas, under different weather and illumina-
tion conditions, has been used to train and test the system. The system shows promising performance on the
database with an overall accuracy of 99.71 %