1,741 research outputs found
Traffic Danger Recognition With Surveillance Cameras Without Training Data
We propose a traffic danger recognition model that works with arbitrary
traffic surveillance cameras to identify and predict car crashes. There are too
many cameras to monitor manually. Therefore, we developed a model to predict
and identify car crashes from surveillance cameras based on a 3D reconstruction
of the road plane and prediction of trajectories. For normal traffic, it
supports real-time proactive safety checks of speeds and distances between
vehicles to provide insights about possible high-risk areas. We achieve good
prediction and recognition of car crashes without using any labeled training
data of crashes. Experiments on the BrnoCompSpeed dataset show that our model
can accurately monitor the road, with mean errors of 1.80% for distance
measurement, 2.77 km/h for speed measurement, 0.24 m for car position
prediction, and 2.53 km/h for speed prediction.Comment: To be published in proceedings of Advanced Video and Signal-based
Surveillance (AVSS), 2018 15th IEEE International Conference on, pp. 378-383,
IEE
Deep Learning for Vanishing Point Detection Using an Inverse Gnomonic Projection
We present a novel approach for vanishing point detection from uncalibrated
monocular images. In contrast to state-of-the-art, we make no a priori
assumptions about the observed scene. Our method is based on a convolutional
neural network (CNN) which does not use natural images, but a Gaussian sphere
representation arising from an inverse gnomonic projection of lines detected in
an image. This allows us to rely on synthetic data for training, eliminating
the need for labelled images. Our method achieves competitive performance on
three horizon estimation benchmark datasets. We further highlight some
additional use cases for which our vanishing point detection algorithm can be
used.Comment: Accepted for publication at German Conference on Pattern Recognition
(GCPR) 2017. This research was supported by German Research Foundation DFG
within Priority Research Programme 1894 "Volunteered Geographic Information:
Interpretation, Visualisation and Social Computing
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