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conferenceseries
.com
Volume 08
Research & Reviews: Journal of Engineering and Technology
ISSN: 2319-9873
Automobile Europe 2019
July 08-09, 2019
6
th
International Conference and Exhibition on
July 08-09, 2019 | Zurich, Switzerland
Automobile & Mechanical Engineering
Towards holistic scene understanding in autonomous driving
Panagiotis Meletis
Eindhoven University of Technology, Netherlands
H
olistic scene understanding is a vital component of the self-driving vehicles of the future. It is crucial that those
vehicles are able to understand and interpret their environment in order to drive safely. This requires precise
detection of surrounding objects (vehicles, humans, traffic objects, nature), discrimination between drivable and
non-drivable surfaces (road, sidewalk, buildings) and segmentation of static and dynamic objects into high-level
semantic classes. In the past, computer vision has tackled these problems separately due to their complexity and high
computational needs. Nowadays, deep learning-based systems are trained on manually annotated datasets to solve
these problems, however they face multiple challenges: 1) the number of the annotated semantic classes are limited
by the available datasets to few dozen decreasing the variety of recognizable objects, 2) the density of annotations
is inversely proportional to the size of the datasets, rendering huge dataset incompatible for precise segmentation,
and 3) detection and segmentation are solved separately, that leads to higher memory and computational demands.
Our research addresses the aforementioned challenges by proposing new methods to: 1) train a single network
on multiple datasets with different semantic classes and different type of annotations, and 2) solve simultaneously
with a single network the problems of detection and semantic segmentation. We have deployed those networks in
our autonomous driving car with real-time performance. We demonstrate state-of-the-art results, together with a
fivefold increase in the number of recognizable classes, and we integrate efficiently detection and segmentation into
a joint panoptic segmentation system, taking important steps towards achieving holistic scene understanding.
Biography
Panagiotis Meletis is in the last year of his PhD in the Signal Processing Systems lab of Eindhoven University of Technology (TU/e). He is a Member of Mobile
Perception Systems research cluster, where he develops image recognition algorithms for its autonomous driving car. He is also a TU/e Ambassador of the TU/e
Communication Department.
p_c_meletis@yahoo.comPanagiotis Meletis, JET 2019, Volume 08