@book{2021:oeljeklaus:an_integra,
title = {An Integrated Approach for Traffic Scene Understanding from Monocular Cameras},
year = {2021},
note = {This thesis investigates methods for traffic scene perception
with monocular cameras for a basic environment model in the context of
automated vehicles. The developed approach is designed with special
attention to the computational limitations present in practical
systems. For this purpose, three different scene representations are
investigated. These consist of the prevalent road topology as the
global scene context, the drivable road area and the detection and
spatial reconstruction of other road users. An approach is developed
that allows for the simultaneous perception of all environment
representations based on a multi-task convolutional neural network.
The obtained results demonstrate the efficiency of the multi-task
approach. In particular, the effects of shareable image features for
the perception of the individual scene representations were found to
improve the computational performance.ContentsNomenclature VII1
Introduction 11.1 Motivation . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . 11.2 Outline and contributions . . . . .
. . . . . . . . . . . . . . . . . . . . . . 52 Related Work and
Fundamental Background 82.1 Advances in CNN...},
edition = {1},
publisher = {VDI Verlag},
address = {Düsseldorf},
series = {Verkehrstechnik/Fahrzeugtechnik},
volume = {815},
author = {Oeljeklaus, Malte}
}