Where to drive: free space detection with one fisheye camera

Tobias Scheck; Adarsh Mallandur; Christian Wiede; Gangolf Hirtz

doi:10.1117/12.2556380

31 January 2020 Where to drive: free space detection with one fisheye camera

Tobias Scheck, Adarsh Mallandur, Christian Wiede, Gangolf Hirtz

Proceedings Volume 11433, Twelfth International Conference on Machine Vision (ICMV 2019); 114332V (2020) https://doi.org/10.1117/12.2556380
Event: Twelfth International Conference on Machine Vision, 2019, Amsterdam, Netherlands

Abstract

The development in the field of autonomous driving goes hand in hand with ever new developments in the field of image processing and machine learning methods. In order to fully exploit the advantages of deep learning, it is necessary to have sufficient labeled training data available. This is especially not the case for omnidirectional fisheye cameras. As a solution, we propose in this paper to use synthetic training data based on Unity3D. A five-pass algorithm is used to create a virtual fisheye camera. This synthetic training data is evaluated for the application of free space detection for different deep learning network architectures. The results indicate that synthetic fisheye images can be used in deep learning context.

Citation Download Citation

Tobias Scheck, Adarsh Mallandur, Christian Wiede, and Gangolf Hirtz "Where to drive: free space detection with one fisheye camera", Proc. SPIE 11433, Twelfth International Conference on Machine Vision (ICMV 2019), 114332V (31 January 2020); https://doi.org/10.1117/12.2556380

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available