19 research outputs found
Is it Raining Outside? Detection of Rainfall using General-Purpose Surveillance Cameras
In integrated surveillance systems based on visual cameras, the mitigation of
adverse weather conditions is an active research topic. Within this field, rain
removal algorithms have been developed that artificially remove rain streaks
from images or video. In order to deploy such rain removal algorithms in a
surveillance setting, one must detect if rain is present in the scene. In this
paper, we design a system for the detection of rainfall by the use of
surveillance cameras. We reimplement the former state-of-the-art method for
rain detection and compare it against a modern CNN-based method by utilizing 3D
convolutions. The two methods are evaluated on our new AAU Visual Rain Dataset
(VIRADA) that consists of 215 hours of general-purpose surveillance video from
two traffic crossings. The results show that the proposed 3D CNN outperforms
the previous state-of-the-art method by a large margin on all metrics, for both
of the traffic crossings. Finally, it is shown that the choice of
region-of-interest has a large influence on performance when trying to
generalize the investigated methods. The AAU VIRADA dataset and our
implementation of the two rain detection algorithms are publicly available at
https://bitbucket.org/aauvap/aau-virada.Comment: 10 pages, 7 figures, CVPR2019 V4AS worksho