Authors:
Belén Luque
;
Josep Ramon Morros
and
Javier Ruiz-Hidalgo
Affiliation:
Universitat Politècnica de Catalunya - BarcelonaTech, Spain
Keyword(s):
Computer Vision, Road Detection, Segmentation, Drones, Neural Networks, CNNs.
Related
Ontology
Subjects/Areas/Topics:
Computer Vision, Visualization and Computer Graphics
;
Image and Video Analysis
;
Segmentation and Grouping
Abstract:
The main goal of this paper is to detect roads from aerial imagery recorded by drones. To achieve this, we
propose a modification of SegNet, a deep fully convolutional neural network for image segmentation. In
order to train this neural network, we have put together a database containing videos of roads from the point
of view of a small commercial drone. Additionally, we have developed an image annotation tool based on
the watershed technique, in order to perform a semi-automatic labeling of the videos in this database. The
experimental results using our modified version of SegNet show a big improvement on the performance of the
neural network when using aerial imagery, obtaining over 90% accuracy.